Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of Gravity Recovery and Climate Experiment terrestrial water storage retrievals to evaluate model estimates by the Australian water resources assessment system

Terrestrial water storage (TWS) estimates retrieved from the Gravity Recovery and Climate Experiment (GRACE) satellite mission were compared to TWS modeled by the Australian Water Resources Assessment (AWRA) system. The aim was to test whether differences could be attributed and used to identify model deficiencies. Data for 2003–2010 were decomposed into the seasonal cycle, linear trends and the remaining de‐trended anomalies before comparing. AWRA tended to have smaller seasonal amplitude than GRACE. GRACE showed a strong (>15 mm yr−1) drying trend in northwest Australia that was associated with a preceding period of unusually wet conditions, whereas weaker drying trends in the southern Murray Basin and southwest Western Australia were associated with relatively dry conditions. AWRA estimated trends were less negative for these regions, while a more positive trend was estimated for areas affected by cyclone Charlotte in 2009. For 2003–2009, a decrease of 7–8 mm yr−1 (50–60 km3 yr−1) was estimated from GRACE, enough to explain 6%–7% of the contemporary rate of global sea level rise. This trend was not reproduced by the model. Agreement between model and data suggested that the GRACE retrieval error estimates are biased high. A scaling coefficient applied to GRACE TWS to reduce the effect of signal leakage appeared to degrade quantitative agreement for some regions. Model aspects identified for improvement included a need for better estimation of rainfall in northwest Australia, and more sophisticated treatment of diffuse groundwater discharge processes and surface‐groundwater connectivity for some regions.
Catastrophic Sector Collapses of Quaternary Volcanoes as Significant Sediment Sources in Japan

The Japanese Islands are tectonically active and humid. Thus, erosion and deposition are the primary processes controlling geomorphic development. Catastrophic sector collapses at volcanoes should be considered significant in this context. This study examines the geomorphological role of volcanic sector collapses in Japan, introducing 58 cases with their respective occurrence ages and volumes (≥ 1×108 m3). We find that the frequency of sector collapses becomes exponentially higher as the collapse magnitude decreases. The total volume of the dissected volcanic edifice caused by catastrophic collapses amounts to ca. 6.4 km3 (640×108 m3) during the last 500 years. This value can be translated into an annual denudation rate of 0.53 mm/y per unit area of the Quaternary volcanoes (ca. 24000 km2), which is comparable to the contemporary denudation rate of non-volcanic mountains in Japan. Therefore, although volcanic sector collapses occur intermittently, we have to consider them as sediment sources that are indispensable to an understanding of geomorphology in Japan.
Measurement of 223Ra and 224Ra in coastal waters using a delayed coincidence counter

We describe a nuclear detector system for measuring low activities of 223Ra and 224Ra in natural waters based on an original design of Giffin et al. (1963). Samples are obtained by adsorbing 223Ra and 224Ra onto a column of MnO2 coated fiber (Mn fiber). The short-lived Rn daughters of 223Ra and 224Ra which recoil from the Mn fiber are swept into a scintillation detector where alpha decays of Rn and Po occur. Signals from the detector are sent to a delayed coincidence circuit, which discriminates decays of the 224Ra daughters, 220Rn and 216Po, from decays of the 223Ra daughters, 219Rn and 215Po. The system is calibrated using 232Th and 227Ac standards with daughters in equilibrium adsorbed on Mn fiber. Results of samples from Tampa Bay, Florida, and the Atchafalaya and Mississippi Rivers mixing zones are reported. The method is extendible to measurements of 227Ac, 231Pa, 228Th, and 228Ra.
Reducing test application time through test data mutation encoding

In this paper we propose a new compression algorithm geared to reduce the time needed to test scan-based designs. Our scheme compresses the test vector set by encoding the bits that need to be flipped in the current test data slice in order to obtain the mutated subsequent test data slice. Exploitation of the overlap in the encoded data by effective traversal search algorithms results in drastic overall compression. The technique we propose can be utilized as not only a stand-alone technique but also can be utilized on test data already compressed, extracting even further compression. The performance of the algorithm is mathematically analyzed and its merits experimentally confirmed on the larger examples of the ISCAS '89 benchmark circuits.
A Critical Review of "A Practical Guide to Select Quality Indicators for Assessing Pareto-Based Search Algorithms in Search-Based Software Engineering": Essay on Quality Indicator Selection for SBSE

This paper presents a critical review of the work published at ICSE'2016 on a practical guide of quality indicator selection for assessing multiobjective solution sets in search-based software engineering (SBSE). This review has two goals. First, we aim at explaining why we disagree with the work at ICSE'2016 and why the reasons behind this disagreement are important to the SBSE community. Second, we aim at providing a more clarified guide of quality indicator selection, serving as a new direction on this particular topic for the SBSE community. In particular, we argue that it does matter which quality indicator to select, whatever in the same quality category or across different categories. This claim is based upon the fundamental goal of multiobjective optimisation — supplying the decision-maker a set of solutions which are the most consistent with their preferences.
Designing business model tooling for business model exploration: An experimental design for evaluation

Disruptive technologies drive enterprises to rethink how to create and capture value by revising their business models (BM). Even in cases that the need for BM innovation is clear, how entrepreneurs can do it and what they need to be changed it is not always obvious. That leads to the need for BM exploration. BM tooling can support this process, however, existing BM tools are not widely focused on the BM exploration. In previous steps of our research, we designed and developed a digital tooling for BM exploration. This RiP paper presents the experimental design we plan to use to evaluate the effects of the tooling on the BM exploration. Initial results and future steps are discussed. We expect to contribute to the BM literature by understanding what features of BM tooling contribute to BM exploration.
Guidelines for Extending the RTP Control Protocol (RTCP)

The RTP Control Protocol (RTCP) is used along with the Real-time Transport Protocol (RTP) to provide a control channel between media senders and receivers. This allows constructing a feedback loop to enable application adaptivity and monitoring, among other uses. The basic reporting mechanisms offered by RTCP are generic, yet quite powerful and suffice to cover a range of uses. This document provides guidelines on extending RTCP if those basic mechanisms prove insufficient.
OReX: Object Reconstruction from Planner Cross-sections Using Neural Fields

Reconstructing 3D shapes from planar cross-sections is a challenge inspired by downstream applications like medical imaging and geographic informatics. The input is an in/out indicator function fully deﬁned on a sparse collection of planes in space, and the output is an interpolation of the indicator function to the entire volume. Previous works addressing this sparse and ill-posed problem either produce low quality results, or rely on additional priors such as target topology, appearance information, or input normal directions. In this paper, we present OReX, a method for 3D shape reconstruction from slices alone, featuring a Neural Field as the interpolation prior. A simple neural network is trained on the input planes to receive a 3D coordinate and return an inside/outside estimate for the query point. This prior is powerful in inducing smoothness and self-similarities. The main challenge for this approach is high-frequency details, as the neural prior is overly smoothing. To alleviate this, we offer an iterative estimation architecture and a hierarchical input sampling scheme that encourage coarse-to-ﬁne training, allowing focusing on high frequencies at later stages. In addition, we identify and analyze a common ripple-like effect stemming from the mesh extraction step. We mitigate it by regularizing the spatial gradients of the indicator function around input in/out boundaries, cutting the problem at the root. Through extensive qualitative and quantitative experimentation, we demonstrate our method is robust, accurate, and scales well with the size of the input. We report state-of-the-art results compared to previous approaches and recent potential solutions, and demonstrate the beneﬁt of our individual contributions through analysis and ablation studies.
Ground and remote estimation of leaf area index in Rocky Mountain forest stands, Kananaskis, Alberta

Leaf area index (LAI) is an important measure of canopy structure that is related to biomass, carbon and energy exchange, and is an important input to ecological and climate change models. LAI can be estimated using algorithms applied to airborne and satellite imagery, with ground-based measurements of LAI being required for calibration and validation. A variety of methods exist for ground-based and remote estimation of LAI, and this can lead to confusion and uncertainty regarding selection of methods, experimental design, and instrumentation. As a contribution towards clarifying these protocols, this paper investigated and compared three optical methods and an allometric technique for ground-based estimation of LAI, and these were related to remote LAI estimates derived from the compact airborne spectrographic imager (casi) using three vegetation indices (normalized difference, weighted difference, and soil-adjusted vegetation indices, or NDVI, WDVI, and SAVI, respectively) and subpixel-scale spectral mixture analysis (SMA). The study was conducted in the Kananaskis region of Alberta in the Canadian Rocky Mountains and considered four species compositions within a montane ecological subregion: lodgepole pine, white spruce, composite deciduous (aspen and balsam poplar), and mixedwood (mixture of deciduous and lodgepole pine or white spruce). LAI data were obtained in the field using a LI-COR, Inc. LAI-2000 instrument, a tracing radiation and architecture of canopies (TRAC) system, an integrated (LAI-2000 and TRAC) method, and an allometric technique that used the ratio of sapwood basal area to leaf area. A subsample of plots was assessed with hemispherical photographs and LAI-2000 data from which similar effective leaf area index (eLAI) values were derived for two of the four species analyzed. The results highlight the importance of ensuring that samples represent the range of stand structures and canopy architecture inherent in the species group being assessed. Foliage clumping was observed to be similar in both coniferous and deciduous species and an important element to measure. LAI estimates were influenced by the field methods used to estimate LAI, species and their canopy architecture, and the form of the vegetation index or subpixel-scale mixing derived from the casi image. Of the three vegetation indices, the SAVI was the statistically strongest predictor of LAI for mixedwood species, but all were poor LAI estimators for lodgepole pine and deciduous species. The subpixel-scale scene fractions from SMA provided the best prediction of LAI for white spruce compared with the three vegetation indices. The result for white spruce provides an encouraging basis for further investigation of SMA as a sampling tool to scale from field to high-resolution airborne and satellite imagery for local to landscape-level biophysical estimation.
A Convergent and Efficient Deep Q Network Algorithm

Despite the empirical success of the deep Q network (DQN) reinforcement learning algorithm and its variants, DQN is still not well understood and it does not guarantee convergence. In this work, we show that DQN can diverge and cease to operate in realistic settings. Although there exist gradient-based convergent methods, we show that they actually have inherent problems in learning behaviour and elucidate why they often fail in practice. To overcome these problems, we propose a convergent DQN algorithm ( C-DQN ) by carefully modifying DQN, and we show that the algorithm is convergent and can work with large discount factors ( ∼ 0 . 9998 ). It learns robustly in difﬁcult settings and can learn several difﬁcult games in the Atari 2600 benchmark where DQN fail, within a moderate computational budget. Our codes have been publicly released and can be used to reproduce our results. 1
Shallow-Marine Ostracods from the Lower Pleistocene Kazusa Group in the Tama Hills, Central Japan, with Their Biogeographical Significance in the Northwest Pacific Ocean

Abstract. This study investigated an early Pleistocene ostracod fauna from the Kazusa Group in the Tama Hills (ca. 1.7-1.4 Ma) along the western side of Tokyo Bay, central Japan. We report for the first time an early Pleistocene ostracod fauna from the Kanto District. This fauna consists of 56 species, with three assemblages defined by Q-mode cluster analysis. The two most abundant species are Bicornucythere bisanensis and Spinileberis quadriaculeata in the assemblage BS, Pontocythere subjaponica and Buntonia hanaii in the assemblage PB, and Loxoconcha ikeyai and Pontocythere subjaponica in the assemblage LP. These assemblages indicate the following depositional environments: (1) the innermost to central area of an inner bay having relatively low salinity (assemblage BS); (2) the outer area of the inner bay and upper-shelf area influenced by open sea water with relatively high salinity (assemblage LP); and (3) the central to outer area of the inner bay having salinity intermediate between that of (1) and (2) (assemblage PB). We also report first occurrences on the Pacific side of Japan near Tokyo Bay for two cryophilic taxa, Laperousecythere robusta and Pectocythere sp. Laperousecythere robusta moved southward from the Japan Sea coast, probably through the Tsugaru Strait before reaching central Japan near Tokyo Bay by 1.6 Ma. Pectocythere sp. might have first appeared around Tokyo Bay during the early Pleistocene by 1.6 Ma. The species content of the assemblage BS suggests that Bicornucythere and Spinileberis commonly inhabited inner-bay areas near Tokyo Bay by 1.6-1.4 Ma at the latest. This fossil fauna does not include inner-bay species of the genera Neomonoceratina and Sinocytheridea. Their absence near Tokyo Bay in the early Pleistocene is consistent with previous palaeobiogeographical findings regarding Japanese bay-dwelling ostracods. These data provide information about the route and timing of the northward or southward migrations of shallow-marine benthos along the Northwest Pacific margin during the late Cenozoic.
Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management

Game theory has proven to be a valuable tool to study strategic electricity consumers enrolled in a demand response (DR) program. Among the different billing mechanisms proposed, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium and we analyze its efficiency by providing a bound on the price of anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this DR framework in a stochastic environment where the parameters depend on forecasts. Numerically, we show the relevance of an online DR procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.
Short‐wavelength lateral variation of a D′ P‐wave reflector beneath the southwestern Pacific

The short‐period vertical‐component data from the Fiji Is. earthquakes recorded by three seismological networks in Japan are analysed to investigate short‐wavelength lateral heterogeneities in D′ layer. A double‐array stacking method, which allows us to combine event and receiver arrays, is applied to the records of each network. Three regions in the D′ layer sampled by the three networks are located at horizontal intervals of a few hundred kilometers. In all three regions, the D′ reflectors are detected. The height of the D′ reflector above the CMB, which is estimated by the differential travel time between PdP (D′ reflection) and P, changes from 270 km to 170 km. This result may suggest that some strong short‐wavelength lateral heterogeneities exist in the D′ layer beneath the southwestern Pacific.
Evaluating Performance of Clone Detection Tools in Detecting Cloned Cochange Candidates

Code reuse by copying and pasting from one place to another place in a codebase is a very common scenario in software development which is also one of the most typical reasons for introducing code clones. There is a huge availability of tools to detect such cloned fragments and a lot of studies have already been done for efficient clone detection. There are also several studies for evaluating those tools considering their clone detection effectiveness. Unfortunately, we find no study which compares different clone detection tools in the perspective of detecting cloned co-change candidates during software evolution. Detecting cloned co-change candidates is essential for clone tracking. In this study, we wanted to explore this dimension of code clone research. We used six promising clone detection tools to identify cloned and non-cloned co-change candidates from six $C$ and Java-based subject systems and evaluated the performance of those clone detection tools in detecting the cloned co-change fragments. Our findings show that a good clone detector may not perform well in detecting cloned co-change candidates. The amount of unique lines covered by a clone detector and the number of detected clone fragments plays an important role in its performance. The findings of this study can enrich a new dimension of code clone research.
Refolding planar polygons

This sketch describes a guaranteed technique for generating intersection-free interpolation sequences between arbitrary, non-intersecting, planar polygons. The computational machinery that ensures against self intersection guides a usersupplied distance heuristic that determines the overall character of the interpolation sequence. Additional control is provided to the user through specifying algebraic constraints that can be enforced throughout the sequence.
Distributionally robust mixed-integer programming with Wasserstein metric: on the value of uncertain data

This study addresses a class of linear mixed-integer programming (MIP) problems that involve uncertainty in the objective function coeﬃcients. The coeﬃcients are assumed to form a random vector, which probability distribution can only be observed through a ﬁnite training data set. Unlike most of the related studies in the literature, we also consider uncertainty in the underlying data set. The data uncertainty is described by a set of linear constraints for each random sample, and the uncertainty in the distribution (for a ﬁxed realization of data) is deﬁned using a type-1 Wasserstein ball centered at the empirical distribution of the data. The overall problem is formulated as a three-level distri-butionally robust optimization (DRO) problem. We prove that for a class of bi-aﬃne loss functions the three-level problem admits a linear MIP reformulation. Furthermore, it turns out that in several important particular cases the three-level problem can be solved reasonably fast by leveraging the nominal MIP problem. Finally, we conduct a computational study, where the out-of-sample performance of our model and computational complexity of the proposed MIP reformulation are explored numerically for several application domains.
Face salient points and eyes tracking for robust drowsiness detection

SUMMARY Measuring a driver's level of attention and drowsiness is fundamental to reducing the number of traffic accidents that often involve bus and truck drivers, who must work for long periods of time under monotonous road conditions. Determining a driver's state of alert in a noninvasive way can be achieved using computer vision techniques. However, two main difficulties must be solved in order to measure drowsiness in a robust way: first, detecting the driver's face location despite variations in pose or illumination; secondly, recognizing the driver's facial cues, such as blinks, yawns, and eyebrow rising. To overcome these challenges, our approach combines the well-known Viola–Jones face detector with the motion analysis of Shi–Tomasi salient features within the face. The location of the eyes and blinking is important to refine the tracking of the driver's head and compute the so-called PERCLOS, which is the percentage of time the eyes are closed over a given time interval. The latter cue is essential for noninvasive driver's alert state estimation as it has a high correlation with drowsiness. To further improve the location of the eyes under different conditions of illumination, the proposed method takes advantage of the high reflectivity of the retina to near infrared illumination employing a camera with an 850 nm wavelength filter. The paper shows that motion analysis of the salient points, in particular cluster mass centers and spatial distributions, yields better head tracking results compared to the state-of-the-art and provides measures of the driver's alert state.
CLX: Towards verifiable PBE data transformation

Effective data analytics on data collected from the real world usually begins with a notoriously expensive pre-processing step of data transformation and wrangling. Programming By Example (PBE) systems have been proposed to automatically infer transformations using simple examples that users provide as hints. However, an important usability issue - verification - limits the effective use of such PBE data transformation systems, since the verification process is often effort-consuming and unreliable. We propose a data transformation paradigm design CLX (pronounced "clicks") with a focus on facilitating verification for end users in a PBE-like data transformation. CLX performs pattern clustering in both input and output data, which allows the user to verify at the pattern level, rather than the data instance level, without having to write any regular expressions, thereby significantly reducing user verification effort. Thereafter, CLX automatically generates transformation programs as regular-expression replace operations that are easy for average users to verify. We experimentally compared the CLX prototype with both FlashFill, a state-of-the-art PBE data transformation tool, and Trifacta, an influential system supporting interactive data transformation. The results show improvements over the state of the art tools in saving user verification effort, without loss of efficiency or expressive power. In a user effort study on data sets of various sizes, when the data size grew by a factor of 30, the user verification time required by the CLX prototype grew by 1.3x whereas that required by FlashFill grew by 11.4x. In another test assessing the users' understanding of the transformation logic - a key ingredient in effective verification - CLX users achieved a success rate about twice that of FlashFill users.