Miracle-dz/UniFAR-FTUs huggingface dataset:
Holocene stalagmite δ18O records in the East Asian monsoon region and their correlation with those in the Indian monsoon region

We compare well-dated Holocene stalagmite δ18O records from the East Asian Summer Monsoon (EASM) region and from the Indian Summer Monsoon (ISM) region. We found that the pattern of latitudinal change of speleothem δ18O values from the Indian monsoon region to the East Asian monsoon region is almost identical to that of modern precipitation. This suggests that the modern moisture transport route from the Indian Ocean to the East Asian monsoon region has existed since at least the early Holocene. The δ18O records from both regions exhibit a remarkably similar trend of variation in that the values are more negative during the early Holocene, rapidly become heavy from the mid-Holocene, and are heaviest during the late Holocene. The stalagmite δ18O changes in the East Asian monsoon region are statistically well correlated with those in the Indian monsoon region, both over the entire Holocene and in detail over the last 2000 years. However, in contrast to the obvious consistency of the δ18O values in all of the speleothem records, both instrumental and historical climate records indicate significant spatial variations in rainfall over eastern China. The early-Holocene strong EASM pattern referred from speleothem δ18O in the East Asian monsoon region is quite different to that of other paleoclimatic records such as Holocene paleosol development in the Chinese Loess Plateau, eolian activity in the northern Chinese sandlands, and lake sediments in EASM-dominated region in China, in which the strongest EASM was documented during the mid-Holocene. These findings suggest that the speleothem δ18O record from the East Asian monsoon region may not record EASM variability, but rather that it is controlled by variations in the isotopic composition of precipitation, which is determined mainly by rainfall variability in the ISM region.
Fuzzing Deep-Learning Libraries via Large Language Models

Deep Learning (DL) systems in recent years have received expo-nential growth in popularity and have become ubiquitous in our everyday life. Such systems are built on top of popular DL libraries, e.g., TensorFlow and PyTorch which provide APIs as building blocks for DL systems. Detecting bugs in these DL libraries is critical for almost all downstream DL systems in ensuring effectiveness and safety for the end users. As such, researchers have started devel-oping various fuzzing or testing techniques targeting DL libraries. Previous work can be mainly classified into API-level fuzzing – focusing on generating inputs for each single API and model-level fuzzing – running complete DL models to identify potential bugs. However, both types of techniques cannot detect bugs that can only be exposed by complex API sequences – API-level fuzzers cannot cover API sequences, while model-level fuzzers can only cover specific API sequence patterns and a small subset of APIs due to complicated input/shape constraints for tensor computations. To address these limitations, we propose LLMFuzz – the first automated approach to directly leveraging Large Pre-trained Language Models (LLMs) to generate input programs for fuzzing DL libraries. LLMs are trained on billions of code snippets and can autoregressively generate human-like code snippets. Our key insight is that modern LLMs can also include numerous code snippets invoking DL library APIs in their training corpora, and thus can implicitly learn the intricate DL API constraints and directly generate/mutate valid DL programs for fuzzing DL libraries. More specifically, we first directly use a generative LLM (e.g., Codex) to generate high-quality seed programs based on input prompts. Then, we leverage an evolutionary fuzzing loop which applies an infilling LLM (e.g., InCoder) to further perform small mutations on the seed programs to generate more diverse API sequences for fuzzing DL libraries. Our experimental results on popular DL libraries demonstrate that LLMFuzz is able to cover 91.11% / 24.09% more APIs and achieve 30.38% / 50.84% higher code coverage than state-of-the-art fuzzers on TensorFlow / PyTorch. Furthermore, LLMFuzz is able to detect 65 bugs, with 41 already confirmed as previously unknown bugs.
Learning a Metacognition for Object Detection

In contrast to object recognition models, humans do not blindly trust their perception when building representations of the world, instead recruiting metacognition to detect percepts that are unreliable or false, such as when we realize that we mistook one object for another. We propose METAGEN, an unsupervised model that enhances object recognition models through a metacognition. Given noisy output from an object-detection model, METAGEN learns a meta-representation of how its perceptual system works and uses it to infer the objects in the world responsible for the detections. METAGEN achieves this by conditioning its inference on basic principles of objects that even human infants understand (known as Spelke principles: object permanence, cohesion, and spatiotemporal continuity). We test METAGEN on a variety of state-of-the-art object detection neural networks. We ﬁnd that METAGEN quickly learns an accurate metacognitive representation of the neural network, and that this improves detection accuracy by ﬁlling in objects that the detection model missed and removing hallucinated objects. This approach enables generalization to out-of-sample data and outperforms comparison models that lack a metacognition.
C ELLULAR N ETWORKS

TCP is known to perform poorly in cellular network environments. Yet, most mobile applications are explicitly built on the conventional TCP stack or implicitly leverage TCP tunnels to various cellular middleboxes, including performance-enhancing proxies, application-specific edge proxies, VPN proxies and NAT boxes. Despite significant advances in the design of new congestion control (CC) protocols for cellular networks, deploying these protocols without bypassing the underlying TCP tunnels has remained a challenging proposition. This paper proposes the design of a new Application Layer Congestion Control (ALCC) framework that allows any new CC protocol to be implemented easily at the application layer, within or above an application-layer protocol that sits atop a legacy TCP stack. It drives it to deliver approximately the same as the native performance. The ALCC socket sits on top of a traditional TCP socket. Still, it can leverage the large congestion windows opened by TCP connections to carefully execute an application-level CC within the window bounds of the underlying TCP connection. This paper demonstrates how ALCC can be applied to three well-known cellular CC protocols: Verus, Copa, and Sprout. For these protocols, ALCC can achieve comparable throughput and delay characteristics (within 3-10%) as the native protocols at the application layer across different networks and traffic conditions. ALCC allows a server-side
Extended YouTube Faces: a Dataset for Heterogeneous Open-Set Face Identification

In this paper, we propose an extension of the famous YouTube Faces (YTF) dataset. In the YTF dataset, the goal was to state whether two videos contained the same subject or not (video-based face verification). We enrich YTF with still images and an identification protocol. In the classic face identification, given a probe image (or video), the correct identity has to be retrieved among the gallery ones; the main peculiarity of such protocol is that each probe identity has a correspondent in the gallery (closed-set). To resemble a realistic and practical scenario, we devised a protocol in which probe identities are not guaranteed to be in the gallery (open-set). Compared to a closed-set identification, the latter is definitely more challenging in as much as the system needs firstly to reject impostors (i.e., probe identities missing from the gallery), and subsequently, if the probe is accepted as genuine, retrieve the correct identity. In our case, the probe set is composed of full-length videos from the original dataset, while the gallery is composed of templates, i.e., sets of still images. To collect the images, an automatic application was developed. The main motivations behind this work can be found in both the lack of open-set identification protocols defined in the literature and the undeniable complexity of such. We also argued that extending an existing and widely used dataset could make its distribution easier and that data heterogeneity would make the problem even more challenging and realistic. We named the dataset Extended YTF (E-YTF). Finally, we report baseline recognition results using two well known DCNN architectures.11The dataset, metadata and protocols are available at https://www.micc. unifi.it/resources/datasets/e-ytf/
Using LIDAR data and airborne spectral images for urban land cover classification based on fuzzy set method

In this paper, we propose an analysis on the combinative effect of high-resolution airborne image and light detection and ranging (LIDAR) data for the classification of complex urban areas. In greater detail, the proposed system is composed of three models briefly. Model one includes an advanced kernelized fuzzy c-means classification method for high-resolution airborne image. The characteristics of LIDAR point cloud are introduced in model two, membership degree function of buildings, vegetations and naked land have been built. In model three, high-resolution image and elevation data form LIDAR point cloud are jointed. Experiment carried out on a complex urban area provide interesting conclusions on the effectiveness and protentialities of the joint use of high-resolution image and LIDAR data. In particular, the elevation data was very effective for the separation of species with similar spectral signatures but different elevation information. Experimental results approve that elevation data can improve classification accuracy in building occupied area obviously.
Tongue‐shaped frontal structure and warm water intrusion in the southern Yellow Sea in winter

[1] In winter, a thermohaline front forms at the Yellow Sea (YS) entrance where the warm and saline Cheju Warm Current (CWC) water meets cold coastal water. The frontal structure, as well as the northwestward intrusion of the warm water, was investigated by analyzing conductivity-temperature-depth (CTD) data, tracks of drifting floats, moored current data, and satellite images. The CWC water advances westward as a tongue with its tip heading westward across the YS entrance, not intruding northward along the deepest part of the YS trough, whereas a secondary warm water band is developed northwestward along the western flank of the trough. Floats in the warm tongue moved northwestward across the western frontal zone where the frontal structure was weak, reflecting the northwestward intrusion along the 50–70 m isobaths through the frontal zone. Currents in the trough do not always meet the upwind flow theory that, in an elongated basin, the wind-driven flow is upwind in the deep channel, but rather show the predominance of the southward downwind flow. Model experiments show that on the western flank of the trough, both the southeastward tide-induced residual flow and the southeastward flow due to the nonlinear effect between tide and wind are generated at the same time. Thus the intermittent intrusion of the CWC across the western frontal zone may be closely associated with the predominance of the upwind flow over the southeastward nonlinear interacted flow.
People in Cities: The Urban Environment and its Effects

Series foreword Preface Part I. The Idea of the City: 1. The city as environment: an introduction 2. Urban characteristics: city versus city and city versus town 3. Definitions and models of urban life 4. The city as I see it: image and activity Part II. Living in the City: 5. The city as too much: crowding, noise, and all that stress 6. Isolation and integration: social relations in the city 7. Cities by design: the physical environment and urban living 8. Can the city be a livable place? References Author Index Subject Index.
A Century of forest management mapping

Abstract Large scale, detailed maps have been produced and maintained by forestry agencies in many parts of central Europe since the mid nineteenth century. This paper describes a series of maps supporting the management of a forest area in Austria from 1872 until 1996. The last edition of this series marks the end of an era of forest mapping based on traditional to surveying and manual cartography. The historical development of this map series is examined in terms of the type and amount of spatial information. It was found that the locational accuracy of the various maps does not significantly vary. Historical forest maps provide a record of past management practice and may therefore be usefully incorporated into spatial information systems to support current management. Several approaches to converting the forest maps of various dates to digital form were tested and found to give some improvement in metric quality. The remaining relative locational disagreements hamper the incorporation of these histori.
Evaluating the temporal understanding of neural networks on event-based action recognition with DVS-Gesture-Chain

Enabling artiﬁcial neural networks (ANNs) to have temporal understanding in visual tasks is an essential requirement in order to achieve complete perception of video sequences. A wide range of benchmark datasets is available to allow for the evaluation of such capabilities when us-ing conventional frame-based video sequences. In contrast, evaluating them for systems targeting neuromorphic data is still a challenge due to the lack of appropriate datasets. In this work we deﬁne a new benchmark task for action recognition in event-based video sequences, DVS-Gesture-Chain (DVS-GC), which is based on the temporal combination of multiple gestures from the widely used DVS-Gesture dataset. This methodology allows to create datasets that are arbitrarily complex in the temporal dimension. Using our newly deﬁned task, we evaluate the spatio-temporal understanding of different feed-forward convolutional ANNs and convolutional Spiking Neural Networks (SNNs). Our study proves how the original DVS Gesture benchmark could be solved by networks without temporal understanding, unlike the new DVS-GC which demands an understanding of the ordering of events. From there, we provide a study showing how certain elements such as spiking neurons or time-dependent weights allow for temporal understanding in feed-forward networks without the need for recurrent connections. Code available at: https://github.com/ VicenteAlex/DVS-Gesture-Chain
A class of graphs of large rankwidth

We describe several graphs of arbitrarily large rankwidth (or equivalently of arbitrarily large cliquewidth). Korpelainen, Lozin, and Mayhill [Split permutation graphs, {\em Graphs and Combinatorics}, 30(3):633--646, 2014] proved that there exist split graphs with Dilworth number~2 of arbitrarily large rankwidth, but without explicitly constructing them. Our construction provides an explicit construction. Maffray, Penev, and Vuskovic [Coloring rings, arXiv:1907.11905, 2019] proved that graphs that they call rings on $n$ sets can be colored in polynomial time. Our construction shows that for some fixed integer $n\geq 3$, there exist rings on $n$ sets of arbitrarily large rankwidth. When $n\geq 5$ and $n$ is odd, this provides a new construction of even-hole-free graphs of arbitrarily large rankwidth.
Xmonad

xmonad is a tiling window manager for the X Window system, implemented, configured and dynamically extensible in Haskell. This demonstration presents the case that software dominated by side effects can be developed with the precision and efficiency we expect from Haskell by utilising purely functional data structures, an expressive type system, extended static checking and property-based testing. In addition, we describe the use of Haskell as an application configuration and extension language.
Relationship between hovering depth and viewing position

Random-dot stereograms first generated by Julesz have since been much used for research in vision and perception. When stereograms are binocularly viewed, three-dimensional surfaces can be perceived hovering over the random-dot background. It can be observed that when the viewing distance alters, the hovering depth of the surface also changes and that if we move our eyes to and fro sideways while viewing, the hovering surface moves with our eye movement. It is believed that the information about depth and three-dimensional shape available from the horizontal component of the stereo disparity field requires interpretation in conjunction with information about egocentric viewing distance. This paper shows the relationship between hovering depth and viewing position. The hovering depth can be calculated providing the interocular distance, the convergence angle and the disparity are known. The ratio of the hovering depths at two different viewing positions is equal to the ratio of the corresponding viewing distances. A mathematical explanation is given of the fact that changing viewing position results in changing of the perceived depth of the hovering surface in stereograms. The horizontal shift of the hovering surface has a linear relationship with the amount of eye movement, and the ratio between them is determined by a the disparity and the interocular distance.
Networked Publics

Digital media and network technologies are now part of everyday life. The Internet has become the backbone of communication, commerce, and media; the ubiquitous mobile phone connects us with others as it removes us from any stable sense of location. Networked Publics examines the ways that the social and cultural shifts created by these technologies have transformed our relationships to (and definitions of) place, culture, politics, and infrastructure. Four chapters--each by an interdisciplinary team of scholars using collaborative software--provide a synoptic overview along with illustrative case studies. The chapter on place describes how digital networks enable us to be present in physical and networked places simultaneously--often at the expense of nondigital commitments. The chapter on culture explores the growth and impact of amateur-produced and remixed content online. The chapter on politics examines the new networked modes of bottom-up political expression and mobilization. And finally, the chapter on infrastructure notes the tension between openness and control in the flow of information, as seen in the current controversy over net neutrality.
Lapita on the Periphery. New data on old problems in the Kingdom of Tonga

Archaeological research in the Kingdom of Tonga over the past four decades illustrates a widespread distribution of Lapita coloniser sites throughout the archipelago. A 1999 re-excavation and assessment of the Nukuleka (To 2) and Ha'ateiho (To 5) sites on Fanga 'Uta Lagoon on the southern island of Tongatapu, as well as survey of the Lapita-age paleoshoreline of the lagoon, provide new insights on old problems relating to first human settlement. The Tongatapu results are compared to Lapita site data recovered from the Ha'apai island group between 1995 and 1997. Inferences subsequently are made on the broader issues of Tongan chronology, settlement progression, material culture technologies, settlement pattern and economy.
Passive Earth Pressure with Critical State Concept

This paper presents experimental data of earth pressure acting against a vertical rigid wall, which moved toward a mass of dry sand. The backfill had been placed in lifts to achieve relative densities of 38, 63, and 80%. The instrumented retaining-wall facility at National Chiao Tung University in Taiwan was used to investigate the effects of soil density on the development of earth pressure. Based on the experimental data, it has been found that the Coulomb and Terzaghi solutions calculated with the peak internal friction angle significantly overestimated the ultimate passive thrust for the retaining wall filled with dense sand. As the wall movementS exceeded 12% of the wall height H, the passive earth thrust would reach a constant value, regardless of the initial density of backfill. Under such a large wall movement, soils along the rupture surface had reached the critical state, and the shearing strength on the surface could be properly represented with the residual internal-friction angle. The ultimate passive earth pressure was successfully estimated by adopting the critical state concept to either Terzaghi or Coulomb theory. CE Database keywords: Passive pressure; Earth pressure; Sand; Vertical angles.
ROI image compression algorithm for reconnaissance satellite systems

The visual effect is an important fact in the coding algorithm. So the saliency of visual attention(SVA) can be used to determine the region of interest(ROI) in the ROI image coding. A novel SVA based ROI(SVA-ROI) image coding scheme is presented for the reconnaissance satellite systems. As the SVA of the original image and reconstructed image are usually the same, the same ROI can be automatically determined in the encoder and decoder with the SVA. Then the ROI side information is no need to be transmitted and the compression efficiency can be improved. Experimental results have demonstrated that SVA-ROI has better visual effect than the similar algorithms, which will be suitable for the reconnaissance satellite systems.
Enhancing Depth Completion with Multi-View Monitored Distillation

 Abstract —This paper presents a novel method for depth completion, which leverages multi-view improved monitored distillation to generate more precise depth maps. Our approach builds upon the state-of-the-art ensemble distillation method, in which we introduce a stereo-based model as a teacher model to improve the accuracy of the student model for depth completion. By minimizing the reconstruction error for a given image during ensemble distillation, we can avoid learning inherent error modes of completion-based teachers. To provide self-supervised information, we also employ multi-view depth consistency and multi-scale minimum reprojection. These techniques utilize existing structural constraints to yield supervised signals for student model training, without requiring costly ground truth depth information. Our extensive experimental evaluation demonstrates that our proposed method significantly improves the accuracy of the baseline monitored distillation method.