Miracle-dz/UniFAR-FTUs huggingface dataset:
Triplet is All You Need with Random Mappings for Unsupervised Visual Representation Learning

Contrastive self-supervised learning (SSL) has achieved great success in unsupervised visual representation learning by maximizing the similarity between two augmented views of the same image (positive pairs) and simultaneously contrasting other different images (negative pairs). However, this type of methods, such as Sim-CLR and MoCo, relies heavily on a large number of negative pairs and thus requires either large batches or memory banks. In contrast, some recent non-contrastive SSL methods, such as BYOL and SimSiam, attempt to discard negative pairs by introducing asymmetry and show remarkable performance. Unfortunately, to avoid collapsed solutions caused by not using negative pairs, these methods require sophisticated asymmetry designs. In this paper, we argue that negative pairs are still necessary but one is sufﬁcient, i.e., triplet is all you need . A simple triplet-based loss can achieve surprisingly good performance without requiring large batches or asymmetry. Moreover, we observe that unsupervised visual representation learning can gain signiﬁcantly from randomness. Based on this observation, we propose a simple plug-in RandOm MApping (ROMA) strategy by randomly mapping samples into other spaces and enforcing these randomly projected samples to satisfy the same correlation requirement. The proposed ROMA strategy not only achieves the state-of-the-art performance in conjunction with the triplet-based loss, but also can further effectively boost other SSL methods.
Two-Stage, Integrated, Geothermal-CO2 Storage Reservoirs: An Approach for Sustainable Energy Production, CO2-Sequestration Security, and Reduced Environmental Risk

We introduce a hybrid two-stage energy-recovery approach to sequester CO{sub 2} and produce geothermal energy at low environmental risk and low cost by integrating geothermal production with CO{sub 2} capture and sequestration (CCS) in saline, sedimentary formations. Our approach combines the benefits of the approach proposed by Buscheck et al. (2011b), which uses brine as the working fluid, with those of the approach first suggested by Brown (2000) and analyzed by Pruess (2006), using CO{sub 2} as the working fluid, and then extended to saline-formation CCS by Randolph and Saar (2011a). During stage one of our hybrid approach, formation brine, which is extracted to provide pressure relief for CO{sub 2} injection, is the working fluid for energy recovery. Produced brine is applied to a consumptive beneficial use: feedstock for fresh water production through desalination, saline cooling water, or make-up water to be injected into a neighboring reservoir operation, such as in Enhanced Geothermal Systems (EGS), where there is often a shortage of a working fluid. For stage one, it is important to find economically feasible disposition options to reduce the volume of brine requiring reinjection in the integrated geothermal-CCS reservoir (Buscheck et al. 2012a). During stage two, which begins as CO{sub 2} reaches the production wells; coproduced brine and CO{sub 2} are the working fluids. We present preliminary reservoir engineering analyses of this approach, using a simple conceptual model of a homogeneous, permeable CO{sub 2} storage formation/geothermal reservoir, bounded by relatively impermeable sealing units. We assess both the CO{sub 2} sequestration capacity and geothermal energy production potential as a function of well spacing between CO{sub 2} injectors and brine/CO{sub 2} producers for various well patterns and for a range of subsurface conditions.
Determining Spatially-Distributed Annual Water Balances for Ungauged Locations on Shikoku Island, Japan: A Comparison of Two Interpolators/Détermination de Bilans Hydriques Spatialisés pour des Sites Non-Jaugés de L'Īle de Shikoku, au Japon: Comparaison de Deux Interpolateurs

Abstract Methods were evaluated for interpolating precipitation (P), evapotranspiration (ET), and runoff (RO) at ungauged points on Shikoku Island, Japan, using data gathered from gauged stations on the same island. Two methods were examined: a “local” cubic spline interpolator, which, for a given point, fitted the function exactly to nearby gauged data points; and a “global” multivariate regression interpolator, which fitted the function to all gauged data points based on their topographic positions (i.e. latitude, longitude, altitude). Local and global interpolators did not generate similar results for P and temperature (T). The spatial density of gauged data points used in the interpolation affected the performance of the interpolators. With any given density of gauged data points included in the interpolation, the local interpolator outperformed the global interpolator. The findings indicate that local interpolators are more accurate predictors of the spatial distribution of water balance components in mountainous regions such as Shikoku Island.
Critical success factors for ERP implementations in Belgian SMEs

Purpose – The purpose of this paper is to examine the critical success factors of ERP implementations in Belgian SMEs and to identify those success factors that are specific to a SME environment.Design/methodology/approach – The authors survey the literature to discover and classify critical success factors that are potentially applicable to small and medium‐sized enterprises. Through a survey and a multiple case study within four Belgian companies, the authors investigate which of these critical success factors apply to SMEs.Findings – The results show that most of the success factors found in the literature apply to SMEs. Nevertheless, distinct differences were found as well. Some factors, such as a clear scope definition and a standardised infrastructure, are not regarded as critical success factors for SMEs. Moreover, SMEs tend to rely relatively heavily on the input of consultants, who they use as a source of knowledge and experience. Moreover, SMEs need to be able to adjust their businesses quickly .
A termination analyzer for Java bytecode based on path-length

It is important to prove that supposedly terminating programs actually terminate, particularly if those programs must be run on critical systems or downloaded into a client such as a mobile phone. Although termination of computer programs is generally undecidable, it is possible and useful to prove termination of a large, nontrivial subset of the terminating programs. In this article, we present our termination analyzer for sequential Java bytecode, based on a program property called path-length. We describe the analyses which are needed before the path-length can be computed such as sharing, cyclicity, and aliasing. Then we formally define the path-length analysis and prove it correct with respect to a reference denotational semantics of the bytecode. We show that a constraint logic program PCLP can be built from the result of the path-length analysis of a Java bytecode program P and formally prove that if PCLP terminates, then P also terminates. Hence a termination prover for constraint logic programs can be applied to prove the termination of P. We conclude with some discussion of the possibilities and limitations of our approach. Ours is the first existing termination analyzer for Java bytecode dealing with any kind of data structures dynamically allocated on the heap and which does not require any help or annotation on the part of the user.
Demonstration of a Prototype for a Conversational Companion for Reminiscing about Images

This paper describes an initial prototype demonstrator of a Companion, designed as a platform for novel approaches to the following: 1) The use of Information Extraction (IE) techniques to extract the content of incoming dialogue utterances after an Automatic Speech Recognition (ASR) phase, 2) The conversion of the input to Resource Descriptor Format (RDF) to allow the generation of new facts from existing ones, under the control of a Dialogue Manger (DM), that also has access to stored knowledge and to open knowledge accessed in real time from the web, all in RDF form, 3) A DM implemented as a stack and network virtual machine that models mixed initiative in dialogue control, and 4) A tuned dialogue act detector based on corpus evidence. The prototype platform was evaluated, and we describe this briefly; it is also designed to support more extensive forms of emotion detection carried by both speech and lexical content, as well as extended forms of machine learning.
A global map of science based on the ISI subject categories

The ISI subject categories classify journals included in the Science Citation Index (SCI). The aggregated journal-journal citation matrix contained in the Journal Citation Reports can be aggregated on the basis of these categories. This leads to an asymmetrical transaction matrix (citing versus cited) which is much more densely populated than the underlying matrix at the journal level. Exploratory factor analysis leads us to opt for a fourteen-factor solution. This solution can easily be interpreted as the disciplinary structure of science. The nested maps of science (corresponding to 14 factors, 172 categories, and 6,164 journals) are brought online at this http URL An analysis of interdisciplinary relations is pursued at three levels of aggregation using the newly added ISI subject category of "Nanoscience & nanotechnology". The journal level provides the finer grained perspective. Errors in the attribution of journals to the ISI subject categories are averaged out so that the factor analysis can reveal the main structures. The mapping of science can, therefore, be comprehensive at the level of ISI subject categories.
Learning with Noisily-labeled Class-imbalanced Data

Real-world large-scale datasets are both noisily labeled and class-imbalanced. The issues seriously hurt the generalization of trained models. It is hence significant to address the simultaneous incorrect labeling and class-imbalance, i.e., the problem of learning with noisy labels on long-tailed data. Previous works develop several methods for the problem. However, they always rely on strong assumptions that are invalid or hard to be checked in practice. In this paper, to handle the problem and address the limitations of prior works, we propose a representation calibration method RCAL. Specifically, RCAL works with the representations extracted by unsupervised contrastive learning. We assume that without incorrect labeling and class imbalance, the representations of instances in each class conform to a multivariate Gaussian distribution, which is much milder and easier to be checked. Based on the assumption, we recover underlying representation distributions from polluted ones resulting from mislabeled and class-imbalanced data. Additional data points are then sampled from the recovered distributions to help generalization. Moreover, during classifier training, representation learning takes advantage of representation robustness brought by contrastive learning, which further improves the classifier performance. Experiments on multiple benchmarks justify our claims and confirm the superiority of the proposed method.
Managing the implementation of an innovative technology in a hospital: a case study

Purpose – The purpose of this paper is to present a model of radio frequency identification (RFID) implementation process in a hospital. The model is developed to fill the lack of models on RFID implementation in a hospital setting.Design/methodology/approach – The case study research and grounded theory approaches are combined. The data are collected through repeat interviews with the hospital's RFID manager and the IT vendor. The data are analysed using the grounded theory approach.Findings – The main finding of the paper is the RFID implementation process model in a hospital. The model consists of key activities that have occurred during the unfreezing, moving and refreezing stages of the implementation.Research limitations/implications – The generalisability of the model may be limited because it is based only on a single hospital's RFID implementation.Practical implications – RFID managers in hospitals need to be aware that the technology's implementation is no different to other types of information.
Recent Advances in Natural Language Generation: A Survey and Classification of the Empirical Literature

Natural Language Generation (NLG) is defined as the systematic approach for producing human understandable natural language text based on non-textual data or from meaning representations. This is a significant area which empowers human-computer interaction. It has also given rise to a variety of theoretical as well as empirical approaches. This paper intends to provide a detailed overview and a classification of the state-of-the-art approaches in Natural Language Generation. The paper explores NLG architectures and tasks classed under document planning, micro-planning and surface realization modules. Additionally, this paper also identifies the gaps existing in the NLG research which require further work in order to make NLG a widely usable technology.
First approach to the selection of lexical units for continuous speech recognition of Basque

The selection of appropriated Lexical Units is an important issue in the Language Model (LM) generation. Word has been used classically as unit in most of the Continuous Speech Recognition systems. However, during the last years proposals of non-word units have begun to appear. Since Basque is an agglutinative language with a certain structure inside the word, the nonword units could be an adequate option. In this work, a statistical analysis of the morphological structure of Basque has been carried out. This analysis shows a slight increment of the rates of confusion in Continuous Speech Recognition Systems due to the great increment of acoustically similar and short units. Finally several proposals of Lexical Units are analyzed to deal with the problem.
On the Secrecy of Publicly Observable Biometric Features: Security Properties of Gait for Mobile Device Pairing

Gait has been proposed as a feature for mobile device pairing across arbitrary positions on the human body. Results indicate that the correlation in gait-based features across different body locations is sufficient to establish secure device pairing. However, the population size of the studies is limited and powerful attackers with e.g. capability of video recording are not considered. We present a concise discussion of security properties of gait-based pairing schemes including a discussion of popular quantization schemes, classification and analysis of attack surfaces, analysis of statistical properties of generated sequences, an entropy analysis, as well as possible threats and security weaknesses of gait-based pairing systems. For one of the schemes considered, we present modifications to fix an identified security flaw. As a general limitation of gait-based authentication or pairing systems, we further demonstrate that an adversary with video support can create key sequences that are sufficiently close to on-body generated acceleration sequences to breach gait-based security mechanisms.
Multifractality in time series is due to temporal correlations

Based on the rigorous mathematical arguments formulated within the Multifractal Detrended Fluctuation Analysis (MFDFA) approach it is shown that in the uncorrelated time series the eﬀects resembling multifractality asymptotically disappear when the length of time series increases. The related eﬀects are also illustrated by numerical simulations. This documents that the genuine multifractality in time series may only result from the long-range temporal correlations and the fatter distribution tails of ﬂuctuations may broaden the width of singularity spectrum only when such correlations are present. The frequently asked question of what makes multifractality in time series - temporal correlations or broad distribution tails - is thus ill posed.
TOUGHREACT: a new code of the TOUGH Family for Non-Isothermal multiphase reactive geochemical transport in variably saturated geologic media

Coupled modeling of subsurface multiphase fluid and heat flow, solute transport and chemical reactions can be used for the assessment of acid mine drainage remediation, waste disposal sites, hydrothermal convection, contaminant transport, and groundwater quality. We have developed a comprehensive numerical simulator, TOUGHREACT, which considers non-isothermal multi-component chemical transport in both liquid and gas phases. A wide range of subsurface thermo-physical-chemical processes is considered under various thermohydrological and geochemical conditions of pressure, temperature, water saturation, and ionic strength. The code can be applied to one-, two- or three-dimensional porous and fractured media with physical and chemical heterogeneity.
Payment for environmental services in agricultural landscapes : economic policies and poverty reduction in developing countries

Contents List of Contributors Part I Introduction and Synthesis Chapter 1 Introduction and Overview David Zilberman, Takumi Sakuyama and Randy Stringer Part II Conceptual Issues and Theoretical Background Chapter 2 Putting Payments for Environmental Services in the Context of Economic Development David Zilberman, Leslie Lipper and Nancy McCarthy Chapter 3 Designing Payments for Environmental Services with Weak Property Rights and External Interests Stefanie Engel and Charles Palmer Chapter 4 Marketing Environmental Services David Zilberman Chapter 5 Experimental Economics and Environmental Services Jason Shogren Chapter 6 Economics Of Carbon Sequestration Projects Involving Smallholders Oscar Cacho Chaper 7 Conservation Payments to Reduce Wildlife Habitat Fragmentation and Disease Risks Richard D. Horan, Jason F. Shogren and Benjamin M. Gramig Part III Case Studies Chapter 8 Payments for Ecosystem Services, Poverty and Sustainability: The Case of Agricultural Soil Carbon Sequestration John Antle and Jeste J. Stoorvogel Chapter 9 Wildlife conservation in Amboseli, Kenya: Paying for nonuse values Erwin Bulte, Randel Boone, Randy Stringer, and Philip K. Thorton Chapter 10 Lessons Learned from Mexico's Payment for Environmental Services Program Jennifer Alix-Garcia, Alain de Janvry, Elisabeth Sadoulet and Juan Manuel Torres Chapter 11 Agricultural Landscape Externalities, Agro-tourism and Rural Poverty Reduction in Morocco Khalil Allali Chapter 12 Wetlands Services in Pallisa Uganda Imelda Nalukenge and JohnAntle Chapter 13 Agrobiodiversity Services and Rice Breeds in The Philippines N. Fuwa Chapter 14 Financing Environmental Services for the Panama Canal (TBC) John Forgach, et al Chapter 15 Human Wildlife Conflicts and Environmental Services in Bhutan Karma Ura, Erwin Bulte and Randy Stringer Technical Appendix Index
PCB and PAH Dynamics in a Small Rural Lake

Sediment traps were deployed for periods of 4−5 weeks between May 1990 and September 1991 at depths of 6.5 and 12.5 m in a 15 m deep, rural U.K. lake. Trap material was quantitatively analyzed for 14 PAH compounds, 43 PCB congeners, particle mass, and C and N contents. Derived depositional fluxes of total PAHs (11.7 mg m-2 yr-1) and total PCBs (289 and 463 μg m-2 yr-1 at 6.5 and 12.5 m, respectively) are at the upper ends of the ranges reported in other comparable studies. The annual fluxes of individual PAH compounds are generally similar to accumula tion rates determined for surface sediments at the same location, indicating the absence of significant recycling. The ratios of annual depositional fluxes to surface sediment accumulation rates are substantially greater than 1 in the case of phenanthrene (2.5) and PCBs (6.5−23). These relatively elevated fluxes combined with a consideration of particle dynamics in the lake suggest significant recycling between the sediments and water column, involving remob.
Observational relationship of climatologic beta drift with large‐scale environmental flows

While many numerical studies suggested that large‐scale environmental flows significantly affect beta drift, this influence was not verified observationally and included in assessing changes of tropical cyclone (TC) tracks under the background of global warming. This study investigates the influence of large‐scale environmental flow on climatologic beta drift in the northern West Pacific using the best track dataset from Joint Typhoon Warming Center (JTWC) and the NCEP monthly reanalysis over the period from 1965 to 2007. Consistent with most previous numerical studies, the meridional shear of zonal wind, vertical shear of zonal wind and meridional gradient of relative vorticity, which are mainly associated with the zonal environmental wind, play an important role in affecting beta drift. For the meridional shear of zonal flows, the northward beta drift in an anticyclonic shear is faster than that in a cyclonic shear. A poleward (equatorward) gradient of relative vorticity leads to faster (slower) westward beta drift than in a resting environment. TCs tend to move to the left of the vector of vertical wind shear.
Holocene millennial to centennial carbonate cyclicity recorded in slope sediments of the Great Bahama Bank and its climatic implications

A 38 m long sediment core (MD992201) retrieved from a water depth of 290 m from the leeward margin of the Great Bahama Bank (GBB; 25°53·49′N, 79°16·34′W) has been investigated for changes in aragonite content. The core covers the Mid to Late Holocene (the past 7230 yr). Sediment lightness (L*‐values) was used as a proxy for aragonite content, based on a high linear correlation (R = 0·93) between the X‐ray diffraction derived aragonite content and L*‐values. The resulting time resolution of the L*‐values derived aragonite content ranges from 1 yr at the base of the core to 4 yr at the top. Detailed time series analysis using Monte Carlo Singular Spectrum Analysis and spectral analysis (Lomb–Scargle Fourier transform) identifies the presence of seven signals with varying amplitudes and wavelengths that could be traced throughout the past 5500 yr. During the first ∼1600 yr of sedimentation the aragonite record is dominated by the initial flooding of the flat‐topped GBB. Superimposed on a multimillennial signal, related to Holocene sea‐level changes, a millennial‐scale fluctuation and five quasi‐periodic oscillations were detected (∼1·3–2 kyr, ∼500–600 yr, ∼380 yr, ∼260 yr, ∼200 yr and ∼100 yr period). Comparisons with other proxies (e.g. tree ring‐Δ14C, 10Be and δ18O in ice cores) provides information on the origin and dynamics of the individual signals. The analysis shows that the ∼200 yr and ∼100 yr signals can be attributed to solar forcing. The ∼260 yr, ∼380 yr and the ∼500–600 yr quasi‐periodic signals are found to be of climatic origin, whereas the millennial scale fluctuations remain enigmatic, although solar forcing mechanisms seem likely. The data show that variability of solar output as well as past oceanographic and atmospheric changes have modulated the Mid to Late Holocene climate, which in turn controlled sediment input variations found in the Holocene wedge leeward of the GBB. Although these periplatform sediments have a rather uniform appearance, they still contain a large variety of subtle sedimentary variations.