Miracle-dz/UniFAR-FTUs huggingface dataset:
Principal component analysis of stacked multi-temporal images for the monitoring of rapid urban expansion in the Pearl River Delta

The Pearl River Delta is experiencing very fast urban growth in recent years which has caused rapid loss of the valuable agricultural land in this fertile region. There is a great need to monitor the rapid urban expansion using remote sensing for urban planning and management purposes. However, it has been well recognized that there is signi®cant over-estimation of land use change in using multi-temporal images for change detection because of inadequate creation of classi®cation signatures. This paper presents a principal component analysis of stacked multi-temporal images method to reduce such errors. The study demonstrates that this method can reduce errors in change detection using multitemporal images and provide a very useful way in monitoring rapid land use changes and urban expansion in the Pearl River Delta and other parts of the world.
The correlation-assisted missing data estimator

We introduce a novel approach to estimation problems in settings with missing data. Our proposal -- the Correlation-Assisted Missing data (CAM) estimator -- works by exploiting the relationship between the observations with missing features and those without missing features in order to obtain improved prediction accuracy. In particular, our theoretical results elucidate general conditions under which the proposed CAM estimator has lower mean squared error than the widely used complete-case approach in a range of estimation problems. We showcase in detail how the CAM estimator can be applied to $U$-Statistics to obtain an unbiased, asymptotically Gaussian estimator that has lower variance than the complete-case $U$-Statistic. Further, in nonparametric density estimation and regression problems, we construct our CAM estimator using kernel functions, and show it has lower asymptotic mean squared error than the corresponding complete-case kernel estimator. We also include practical demonstrations throughout the paper using simulated data and the Terneuzen birth cohort and Brandsma datasets available from CRAN.
Evaluation of glycine betaine as an inhibitor of dissolved dimethylsulfoniopropionate degradation in coastal waters

Dimethylsulfon~opropionate (DMSP) is an organic sulfur compound which is produced by many marine phytoplankton and which is ubiquitous in the euphotlc zone of the ocean. DMSP is degraded through complex interactions within the food web and studies of its dynamics may lead to greater understanding of microbial ecology and food web interactions. In this study we examined the degradation of dissolved DMSP [DMSP(d)] in coastal water samples and tested glycine betaine (GBT), a structural analog of DMSP, as a potential inhibitor of this important biogeochemical reaction. The addition of 1 to 50 pM GBT to water samples from the northern Gulf of Mexico strongly inhibited the consumption of 50 nM added DMSP(d). The production of dimethyl sulfide (DMS) from DMSP(d) was also inhibited by GBT, but was slightly less sens~tive than overall DMSP degradation. The inhibitory effects of GBT were short-lived, lasting only 5 to 6 h, after which time net DMSP(d) consumption resumed. Several analogs of GBT were also found to be inhibitory to DMSP(d) degradation but unrelated compounds had no effects. Consistent with the inhibitory effects of GBT, we found that endogenous DMSP(d) concentrations increased at steady rates in response to GBT additions. These GBT-induced accumulation rates ranged from 4 to 28 nM d-' in water samples collected over the course of a year and may represent the natural turnover rates of DMSP(d). We found no significant effects of GBT on particulate DMSP concentrations in natural water samples or in an axenic culture of the prasinophyte Tetraselmis subcordiformis. However, addition of 50 pM GBT to the phytoplankton culture caused an accumulation of DMSP(d) (equivalent to 2% of the particulate DMSP in the culture) for a period of 1 h with no change thereafter. GBT may be a useful inhibitor of DMSP(d) degradation (and DMS production) under some circumstances. However, the short-lived inhibitory effects of GBT and the potential for it to cause some direct release from the particulate DMSP pool may limit its application.
The Bow-Tie Centrality: A Novel Measure for Directed and Weighted Networks with an Intrinsic Node Property

Today, there exist many centrality measures for assessing the importance of nodes in a network as a function of their position and the underlying topology. One class of such measures builds on eigenvector centrality, where the importance of a node is derived from the importance of its neighboring nodes. For directed and weighted complex networks, where the nodes can carry some intrinsic property value, there have been centrality measures proposed that are variants of eigenvector centrality. However, these expressions all suffer from shortcomings. Here, an extension of such centrality measures is presented that remedies all previously encountered issues. While similar improved centrality measures have been proposed as algorithmic recipes, the novel quantity that is presented here is a purely analytical expression, only utilizing the adjacency matrix and the vector of node values. The derivation of the new centrality measure is motivated in detail. Specifically, the centrality itself is ideal for the analysis of directed and weighted networks (with node properties) displaying a bow-tie topology. The novel bow-tie centrality is then computed for a unique and extensive real-world dataset, coming from economics. It is shown how the bow-tie centrality assesses the relevance of nodes similarly to other eigenvector centrality measures, while not being plagued by their drawbacks in the presence of cycles in the network.
Lipschitz-Volume Rigidity and Globalization

Let $X$ and $Y$ be length metric spaces. Let $\mathcal H^n$ denote the $n$-dimensional Hausdorff measure. The Lipschitz-Volume Rigidity is a property that if there exists a 1-Lipschitz map $f\colon X\to Y$ and $0<\mathcal H^n(X)=\mathcal H^n(f(X))<\infty$, then $f$ preserves the length of path. This property holds for smooth manifolds but doesn't hold for all singular spaces. We survey the Lipschitz-Volume Rigidity Theorems on singular spaces with lower curvature bounds and discuss some related open problems.
FOR EFFICIENT COMMUNICATION OF ROUTE DIRECTIONS

We can observe that people familiar with an environment give route direc tions of varying granularity to other locals. Such route directions are typically shorter than the turn based directions of current naviga tion services, and contain only references of high relevance to the wayfinder. Studying these route directions of varying granularity re veals that they are intended to be memorized, a property that requires a low cognitive workload of the wayfinder during their usage. T h short-term memory span of humans imposes a limit on the amount and the structure of information communicated. We argue that ro ute directions of varying granularity provide the means to respect these limits by efficient recoding.
Wild rabbit restocking: Suitable acclimation conditions foster adaptive behaviour and improve survival of captive reared rabbits

Wild rabbit is a very important species in the Mediterranean region. Its relevance is both ecological, being a keystone species —prey for several predators— and economic, as it is the most important and the most managed small game species among mammals in the Iberian Peninsula. Although both researchers and game managers claim restocking operations have moderate to low success, it is still one of the management measures often used by conservationists and hunters to recover or boost wild rabbit populations. The high mortality usually verified in the first days after release is the main limiting factor in rabbit restocking. Based on practical research, protocols have improved, pointing out good practices and suggestions to increase success. Adopting soft instead of hard-release protocols has been proven to increase short-term survival after liberation. Aware that purchased rabbits seldom display a quick adaptation to the field, we performed two restocking experiments with different conditions (acclimation period and park size) in order to compare the outcomes in terms of survival rate. The rabbit batch that experienced a longer acclimation period in a larger park showed higher survival rates, as well as more frequent and much larger spatial movements. These results suggest that proper conditions during acclimation may contribute to the success of wild rabbit restocking operations.
Invasive potential of herbaceous Asteraceae in mountainous regions

Up to now we lack experimental evidence on how strongly changing environmental factors limit plant invasions into higher temperate mountains and to what degree the effects of such environmental constraints are dependent on the genetic predisposition of the invasive plants. In this study, we analyzed the responses of four invasive Asteraceae forbs to changes in environmental conditions and variation in interspecific competition along altitudinal gradients in the southwestern Swiss Alps (Valais). In three common gardens at different altitudes, we compared growth, development and reproduction of planted juveniles grown from seed of native (North American) and introduced (European) populations and of different altitude origin. The altitudinal range for establishment and reproduction of the individuals was mostly not substantially different between individuals from the introduced range and from the native range, at least under low competition. Growth constraints through competition by the native matrix vegetation mostly reduced growth, development and reproduction of the individuals from both ranges similarly, narrowing the potential altitudinal distribution in two of the four species investigated. Individuals of several species showed performance differences among different regional origins or among altitude origins. However, such differences were rather evident at low than at higher altitudes. Accordingly, we found only weak evidence for genetic adaptation between individuals from low and high altitudes in our set of species. However, there was a tendency for plants of high altitude origin to show reduced performance at lower altitudes than plants of low altitudinal origin. Our results provide evidence that primarily high phenotypic flexibility (tolerance of wide ranges of environmental conditions) allows invasion of Asteraceae forbs along a wide altitudinal range. However, region of origin and, to a lesser degree, local adaptation of the plants to specific positions along an environmental gradient in the introduced area may influence the invasiveness of the species.
Spiral arms in the protoplanetary disc HD100453 detected with ALMA: evidence for binary–disc interaction and a vertical temperature gradient

Scattered light high-resolution imaging of the protoplanetary disc orbiting HD100453 shows two symmetric spiral arms, possibly launched by an external stellar companion. In this paper, we present new, sensitive high-resolution (∼30 mas) Band 7 ALMA observations of this source. This is the first source where we find counterparts in the sub-mm continuum to both scattered light spirals. The CO J = 3–2 emission line also shows two spiral arms; in this case, they can be traced over a more extended radial range, indicating that the southern spiral arm connects to the companion position. This is clear evidence that the companion is responsible for launching the spirals. The pitch angle of the submillimetre continuum spirals (∼6°) is lower than the one in scattered light (∼16°). We show that hydrodynamical simulations of binary–disc interaction can account for the difference in pitch angle only if one takes into account that the mid-plane is colder than the upper layers of the disc, as expected for the case of externally irradiated discs.
Improving Bidirectional Decoding with Dynamic Target Semantics in Neural Machine Translation

Generally, Neural Machine Translation models generate target words in a left-to-right (L2R) manner and fail to exploit any future (right) semantics information, which usually produces an unbalanced translation. Recent works attempt to utilize the right-to-left (R2L) decoder in bidirectional decoding to alleviate this problem. In this paper, we propose a novel \textbf{D}ynamic \textbf{I}nteraction \textbf{M}odule (\textbf{DIM}) to dynamically exploit target semantics from R2L translation for enhancing the L2R translation quality. Different from other bidirectional decoding approaches, DIM firstly extracts helpful target information through addressing and reading operations, then updates target semantics for tracking the interactive history. Additionally, we further introduce an \textbf{agreement regularization} term into the training objective to narrow the gap between L2R and R2L translations. Experimental results on NIST Chinese$\Rightarrow$English and WMT'16 English$\Rightarrow$Romanian translation tasks show that our system achieves significant improvements over baseline systems, which also reaches comparable results compared to the state-of-the-art Transformer model with much fewer parameters of it.
Fate of bacterial production in a heterotrophic ecosystem: grazing by protists and metazoans in the Hudson Estuary

The Hudson River Estuary IS a heterotrophic ecosystem with high rates of planktonic bacterial production. We measured grazing on bacteria in monthly experiments dunng 1990 to determine: ( l ) the prlmary consumers of bacteria; (2) whether absolute rates of grazing on bacteria were high relative to other systems; and (3) whether bacterla were a sufficient carbon resource for consumers. Fluorescent minicells were used to measure the Ingestion of bacteria by heterotrophic flagellates and ciliates. Using the abundances of bacteria, rotifers and cladocerans in the river, we also estimated zooplankton clearance rates. Total grazing of the plankton community was assessed by measuring the disappearance of fluorescent minicells over 24 and 48 h. Heterotrophic flagellates were the primary consumers of bacteria with ciliates and the cladoceran Bosmina longirostris also important seasonally. Ingestion of bacteria by heterotrophic flagellates, ciliates, and B. longirostris was sufficient at most times to satisfy estimated carbon requirements of these consumers. Large bacterial size and relatively low consumer populations in the Hudson account for the apparent sufficiency of bacteria as a carbon source We conclude that grazing on bacteria in the Hudson River is similar to the levels of grazlng observed in other systems. Nevertheless, bacteria are a potentially significant resource, because the domlnant planktonic consumers are capable of ~ngesting bacteria at rates sufficient to support carbon demands.
Fragmentation in a Primordial Accretion Flow

Under rapid cooling from molecular hydrogen, the accretion disks around Population III (PopIII) stars are believed to fragment, resulting in multiple accreting cores. In this paper, we build a theoretical framework for calculating the optical depth of H$_2$ ro-vibrational line cooling based on the vertical structure in these accretion disks. Applying this physically motivated prescription for the optical depth, we find that cooling in the inner disk with $r \lesssim 10 {\rm\ AU}$ is attenuated significantly as a result of high surface density; $PdV$ heating becomes more efficient than cooling, which prevents fragmentation in the inner disk. Despite this, cooling becomes dynamically important in the outer disk, favoring fragmentation. We argue that most of the resultant fragments are initially at the outer disk, and that any surviving fragment has to migrate slower than the disk-scale photo-evaporation process. Since type I migration is fast, migration slows down as a result of gap-opening in the disk structure. Two possible processes for gap-opening are studied: (1) through a massive, densely-cored ($\rho \gtrsim 10^{-8} {\rm\ g\ cm^{-3}}$) clump able to radiate away the excess gravitational potential energy, and (2) through a fast-growing central star, with $\dot{M} \gtrsim 2 \times 10^{-3} \, M_\odot {\rm\ yr^{-1}}$, whose gravity dominates the star-disk system and favors gap opening.
Are Few-shot Learning Benchmarks Too Simple ?

We argue that the widely used Omniglot and miniImageNet benchmarks are too simple because their *class semantics* do not vary across episodes, which defeats their intended purpose of evaluating few-shot classification methods. The class semantics of Omniglot is invariably "characters" and the class semantics of miniImageNet, "object category". Because the class semantics are so similar, we propose a new method called Centroid Networks which can achieve surprisingly high accuracies on Omniglot and miniImageNet without using any labels at meta-evaluation time. Our results suggest that those benchmarks are not adapted for supervised few-shot classification since the supervision itself is not necessary during meta-evaluation. The Meta-Dataset, a collection of 10 datasets, was recently proposed as a harder few-shot classification benchmark. Using our method, we derive a new metric, the Class Semantics Consistency Criterion, and use it to quantify the difficulty of Meta-Dataset. Finally, under some restrictive assumptions, we show that Centroid Networks is faster and more accurate than a state-of-the-art learning-to-cluster method (Hsu et al 2018).
Privacy-Preserving Causal Inference via Inverse Probability Weighting

The use of inverse probability weighting (IPW) methods to estimate the causal effect of treatments from observational studies is widespread in econometrics, medicine and social sciences. Although these studies often involve sensitive information, thus far there has been no work on privacy-preserving IPW methods. We address this by providing a novel framework for privacy-preserving IPW (PP-IPW) methods. We include a theoretical analysis of the effects of our proposed privatisation procedure on the estimated average treatment effect, and evaluate our PP-IPW framework on synthetic, semi-synthetic and real datasets. The empirical results are consistent with our theoretical findings.
Can Investors Benefit From Using Morningstar’s Stewardship Grades?

Interest in governance led Morningstar to develop a summary measure for mutual fund governance. In contrast to previous work in this area, we focus on whether and how individual investors can use the Stewardship Grade Overall to improve mutual fund selection. We find that regardless of fee structure, top overall governance grade funds impose lower costs on investors regardless of fund investment style. We also find some evidence that choosing funds with the highest stewardship grade may earn positive risk adjusted returns. Stewardship Grade overall may therefore help less sophisticated investors identify better-performing mutual funds.
Variations in Leaf morphology of Baobab (Adansonia digitata L) in Sudan

Adansonia digitata L. is an important tree for the livelihood of people in arid zones. Therefore, selection of superior phenotypes of leaves and fruit trees and products is essential for future species cultivation and conservation. Thus the objective of this study was to characterize and assess leaf morphology of Adansonia digitata in relation to fruit morphology and location. Five to twenty individuals’ trees were sampled randomly within baobab population for morphometric measurements. From each tree, six fresh leaves without any damage were selected from different positions of tree crown and kept in labeled plastic bags. It was characterized for leaf size, thickness, and stomata density on the abaxial surface of leaves. Variations analysis was employed using SPSS and Excel programs. Our preliminary results indicated high significant variations in leaves characters (medial leaflet length, leaflet width, number of leaflet and medial leaflet thickness) and stomata density. Higher stomata density was found in North Kordofan state (101.36±14.77), dry area compared to those from Blue Nile state (83.36±12.95) wetter area. Trees from Blue Nile state study site showed greater leaves size than those from North Kordofan state. It seems that environment may play a role in baobab trees leaves morphology. However, additional research on tree genetics is necessary to complement the baobab resources cultivation and conservation. Keywords: Leaf morphology, Adansonia digitata , Stomata density, Rainfall.
Modulated interlayer exciton properties in a two-dimensional moiré crystal

Based on first-principles calculations and $\mathbit{k}\ifmmode\cdot\else\textperiodcentered\fi{}\mathbit{p}$ model analyses, we uncover the coexistence and coupling of Rashba spin splitting with electronic ferroelectricity in bilayer transition metal dichalcogenides $M{X}_{2}$ ($M=\text{Mo,W}$; $X=\text{S,Se,Te}$) with certain stacking configurations. The reversible spontaneous ferroelectric polarization, along the out-of-plane direction (the preferred direction for applications), totally arises from the interlayer charge transfer, rather than being governed by the ionic displacement as found in conventional ferroelectrics. The spin texture related to the Rashba spin splitting can be reversed upon inversion of the ferroelectric polarization. In particular, by applying a small in-plane compressive strain, the magnitude of Rashba band splitting can be tuned to be as large as 100 meV. These results would open up possibilities for exploring two-dimensional multiferroic physics and developing electrically controlled nanoscale spintronic devices.
Memory Requirement Reduction of Deep Neural Networks Using Low-bit Quantization of Parameters

Effective employment of deep neural networks (DNNs) in mobile devices and embedded systems is hampered by requirements for memory and computational power. This paper presents a non-uniform quantization approach which allows for dynamic quantization of DNN parameters for different layers and within the same layer. A virtual bit shift (VBS) scheme is also proposed to improve the accuracy of the proposed scheme. Our method reduces the memory requirements, preserving the performance of the network. The performance of our method is validated in a speech enhancement application, where a fully connected DNN is used to predict the clean speech spectrum from the input noisy speech spectrum. A DNN is optimized and its memory footprint and performance are evaluated using the short-time objective intelligibility, STOI, metric. The application of the low-bit quantization allows a 50% reduction of the DNN memory footprint while the STOI performance drops only by 2.7%.
Modulating Surrogates for Bayesian Optimization

Bayesian optimization (BO) methods often rely on the assumption that the objective function is well-behaved, but in practice the objective functions are seldom well-behaved even if noise-free observations can be collected. We propose to address the issue by focusing on the well-behaved structure informative for search while ignoring detrimental structure that is challenging to model data efficiently. We use a noise distribution to absorb the challenging details by treating them as irreducible uncertainty. In particular we use a latent Gaussian process as the surrogate model, in which a latent variable is introduced to the input of a Gaussian process and serves as a noise variable. It allows the noise distribution to be non-stationary and non-Gaussian. With experiments on a range of BO benchmarks, we show that our method significantly outperform existing methods. Keywords: robust surrogate models, Bayesian Optimization, nonsmooth objective functions, Latent Gaussian Processes