Miracle-dz/UniFAR-FTUs huggingface dataset:
A new method for modelling flow duration curves and predicting streamflow regimes under altered land-use conditions / Une nouvelle méthode de modélisation des courbes de débits classés et de prévision des régimes d'écoulement sous conditions modifiées d'occupation du sol

Abstract The impact of changes in land-use/cover on streamflow at short time scales is evaluated by examining the changes in the flow duration curve (FDC) before and after land-use/cover change. The FDC characterizes the relationship between the magnitude and frequency and hence provides the complete range of streamflow over time. Two issues need to be considered in predicting the FDC due to land-use changes: (a) the appropriate parametric form of the FDC that enables application of the same expression of FDCs before and after the changes; and (b) the ability of parameters to capture and characterize the effect of land-use changes. In this paper, we propose a model which is a four-parameter double power form as a function of the FDC, where the two hydrological parameters represent the mean annual flow ([Qbar]) and the cease-to-flow point (τ expressed as a percentage), while the other two parameters (α and β) determine the shape of the FDC. The properties of this function are investigated in order to assign parameters to cope with the land-use changes. The model is used for several typical catchments in Australia for demonstration.
A new application of a multifrequency submillimeter radiometer in determining the microphysical and macrophysical properties of volcanic plumes: A sensitivity study

[1] In this paper, the potential of a multifrequency submillimeter radiometer to characterize ash plumes in the near-field of a volcanic eruption is evaluated. The radiometer's sensitivity to mass concentration and particle effective dimension is shown to depend most critically on aerosol altitude and ejected water vapor concentration. There is also some dependence on temperature, aerosol shape and complex refractive index. For this study, the volcanic aerosols are assumed to be randomly oriented solid hexagonal silicates of aspect ratio unity. The T-matrix method is used to calculate the single-scattering properties of the aerosols at 36 frequencies between 90 GHz and 880 GHz, and the aerosol bulk scattering properties are derived assuming lognormal size distribution functions. A midlatitude standard summer atmosphere and a perturbed midlatitude summer atmosphere are used to quantify the sensitivity, using the delta-Eddington two-stream approximation, of the radiometer to the presence of aerosol. It is shown that at 34 frequencies, between 113 GHz and 880 GHz, the sensitivity to aerosol is a maximum if the following four conditions are satisfied: (i) The altitude of the aerosol layer should be ≫ 3 km, (ii) 0.1 g m−3 < mass concentration < 30 g m−3 (iii) the aerosol effective dimension, De, 20 μm < De < 1000 μm and (iv) water vapor ejected by a volcano into the atmosphere should be < 1000 times greater than the background water vapor concentration. The paper demonstrates the potential usefulness of using spectrally resolved submillimeter measurements in the near-field of volcanic eruptions to characterize plume properties.
Investment in Two-Sided Markets and the Net Neutrality Debate

Abstract This paper develops a game-theoretic model based on a two-sided market framework to compare Internet service providers’ (ISPs) investment incentives, content providers’ (CPs) participation, and social welfare between neutral and non-neutral network regimes. We find that ISPs’ investments are driven by the trade-off between softening consumer price competition and increasing revenues from CPs. Specifically, investments are higher in the non-neutral regime because it is easier to extract revenue through appropriate CP pricing. On the other hand, participation of CPs may be reduced in a non-neutral network due to higher prices. The net impact of non-neutrality on social welfare is determined by which of these two effects is dominant. Overall, we find that the non-neutral network is always welfare superior in a “walled-gardens” model, while the neutral network is superior in a “priority lanes” model when CP-quality heterogeneity is large. These results provide useful insights that inform the net-neutrality debate.
Early Periodic Register Allocation on ILP Processors

Register allocation in loops is generally performed after or during the software pipelining process. This is because doing a conventional register allocation as a first step without assuming a schedule lacks the information of interferences between values live ranges. Thus, the register allocator may introduce an excessive amount of false dependences that dramatically reduce the ILP (Instruction Level Parallelism). We present a new theoretical framework for controlling the register pressure before software pipelining. This is based on inserting some anti-dependence edges (register reuse edges) labeled with reuse distances, directly on the data dependence graph. In this new graph, we are able to fix the register pressure, measured as the number of simultaneously alive variables in any schedule. The determination of register and distance reuse is parameterized by the desired minimum initiation interval (MII) as well as by the register pressure constraints - either can be minimized while the other one is fixed. After scheduling, register allocation is done on conventional register sets or on rotating register files. We give an optimal exact model, and an approximation that generalizes the Ning-Gao [22] buffer optimization method. We provide experimental results which show good improvement compared to [22]. Our theoretical model considers superscalar, VLIW and EPIC/IA64 processors.
Tree ring evidence of a 20th century precipitation surge in the monsoon shadow zone of the western Himalaya, India

[1] The present study is the first attempt to develop an annual (August-July) precipitation series back to AD 1330 using a tree ring data network of Himalayan cedar (Cedrus deodara (Roxb.) G. Don) from the Lahaul-Spiti region in the western Himalaya, India. The rainfall reconstruction reveals high magnitude multidecadal droughts during the 14th and 15th centuries and thenceforth a gradual increase in precipitation. Increasingly wet conditions during the 20th century are consistent with other long-term precipitation reconstructions from high Asia and reflect a large-scale intensification of the hydrological cycle, coincident with what is anticipated due to global warming. Significant relationships between reconstructed precipitation and precipitation records from central southwest Asia, east of the Caspian Sea, ENSO (NINO4-SST) variability and summer monsoon rainfall over central northeast India underscore the utility of our data in synoptic climatology.
Lebenschancen

Wenn man Dahrendorfs neues Buch gelesen hat, kann man die Gelegenheit seiner Besprechung als eine Chance begreifen — wenn auch nicht als Lebenschance, so doch als Chance zur Kritik. Allerdings bietet es dazu so viele Ansatzpunkte und Möglichkeiten, sprich „Optionen" an, daß man sich als Rezensent schon an seine Verpflichtungen und Grenzen, Dahrendorfs „Ligaturen", erinnern und halten muß, um den richtigen Weg zu finden. In diesem Dilemma ist eine kurze Inhaltsangabe der sieben Kapitel des Buches vielleicht der beste Ausgangspunkt.
Exemplar Fine-Tuning for 3D Human Pose Fitting Towards In-the-Wild 3D Human Pose Estimation

We propose a method for building large collections of human poses with full 3D annotations captured `in the wild', for which specialized capture equipment cannot be used. We start with a dataset with 2D keypoint annotations such as COCO and MPII and generates corresponding 3D poses. This is done via Exemplar Fine-Tuning (EFT), a new method to fit a 3D parametric model to 2D keypoints. EFT is accurate and can exploit a data-driven pose prior to resolve the depth reconstruction ambiguity that comes from using only 2D observations as input. We use EFT to augment these large in-the-wild datasets with plausible and accurate 3D pose annotations. We then use this data to strongly supervise a 3D pose regression network, achieving state-of-the-art results in standard benchmarks, including the ones collected outdoor. This network also achieves unprecedented 3D pose estimation quality on extremely challenging Internet videos.
Inverse method analysis in optothermal skin measurements

We present a new scheme for the inverse analysis of opto- thermal transients that is able to calculate initial temperature profiles from noisy data, despite the ill- conditioning. It is particularly useful for tackling problems where the inhomogeneities of the sample are insufficiently well understood, such as the diffusion of externally applied substances through skin or skin pigment depth profiling. We present the mathematical approach, supported with examples of analyses of in-vivo opto-thermal measurements.
Very high resolution image matching based on local features and k‐means clustering

Image matching is a critical process in photogrammetry and remote sensing. Automatic and reliable feature matching using well‐distributed points in very high resolution images is a difficult task due to significant relief displacement caused by tall buildings and ground relief. In this paper a robust and efficient image‐matching approach is proposed, consisting of two main steps. In the first step, three sets of local features – Harris points, UR‐SIFT and MSER – are extracted over the entire image. A SIFT (scale‐invariant feature transform) descriptor is then created for each extracted feature, and an initial cross‐matching verification is performed using the Euclidean distance between feature descriptors. In the second step, an approach based on k‐means clustering is performed to achieve accurate matching without mismatched features, followed by a consistency check using a local affine transformation model for each cluster. The proposed method is successfully applied to matching various aerial and satellite images and the results demonstrate its robustness and capability.
Evaluation of aerosol mixing state classes in the GISS modelE‐MATRIX climate model using single‐particle mass spectrometry measurements

Aerosol particles in the atmosphere are composed of multiple chemical species. The aerosol mixing state, which describes how chemical species are mixed at the single‐particle level, provides critical information on microphysical characteristics that determine the interaction of aerosols with the climate system. The evaluation of mixing state has become the next challenge. This study uses aerosol time‐of‐flight mass spectrometry (ATOFMS) data and compares the results to those of the Goddard Institute for Space Studies modelE‐MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) model, a global climate model that includes a detailed aerosol microphysical scheme. We use data from field campaigns that examine a variety of air mass regimens (urban, rural, and maritime). At all locations, polluted areas in California (Riverside, La Jolla, and Long Beach), a remote location in the Sierra Nevada Mountains (Sugar Pine) and observations from Jeju (South Korea), the majority of aerosol species are internally mixed. Coarse aerosol particles, those above 1 µm, are typically aged, such as coated dust or reacted sea‐salt particles. Particles below 1 µm contain large fractions of organic material, internally mixed with sulfate and black carbon, and few external mixtures. We conclude that observations taken over multiple weeks characterize typical air mass types at a given location well; however, due to the instrumentation, we could not evaluate mass budgets. These results represent the first detailed comparison of single‐particle mixing states in a global climate model with real‐time single‐particle mass spectrometry data, an important step in improving the representation of mixing state in global climate models.
Principles for Macro Ethics of Sociotechnical Systems: Taxonomy and Future Directions

The rapid adoption of artiﬁcial intelligence (AI) necessitates careful analysis of its ethical implications. In addressing ethics and fairness implications, it is important to examine the whole range of ethically relevant features rather than looking at individual agents alone. This can be accomplished by shifting perspective to the systems in which agents are embedded, which is encapsulated in the macro ethics of sociotechnical systems (STS). Through the lens of macro ethics, the governance of systems — which is where participants try to promote outcomes and norms which reﬂect their values — is key. However, multiple-user social dilemmas arise in an STS when stakeholders of the STS have diﬀerent value preferences or when norms in the STS conﬂict. To develop equitable governance which meets the needs of diﬀerent stakeholders, and resolve these dilemmas in satisfactory ways with a higher goal of fairness, we need to integrate a variety of normative ethical principles in reasoning. Normative ethical principles are understood as operationalizable rules inferred from philosophical theories. A taxonomy of ethical principles is thus beneﬁcial to enable practitioners to utilise them in reasoning. This work develops a taxonomy of normative ethical principles which can be operationalized in the governance of STS. We identify an array of ethical principles, with 25 nodes on the taxonomy tree. We describe the ways in which each principle has previously been operationalized, and suggest how the operationalization of principles may be applied to the macro ethics of STS. We further explain potential diﬃculties that may arise with each principle. We envision this taxonomy will facilitate the development of methodologies to incorporate ethical principles in reasoning capacities for governing equitable STS.
Profile for Datagram Congestion Control Protocol (DCCP) Congestion Control ID 2: TCP-like Congestion Control

This document contains the profile for Congestion Control Identifier 2 (CCID 2), TCP-like Congestion Control, in the Datagram Congestion Control Protocol (DCCP). CCID 2 should be used by senders who would like to take advantage of the available bandwidth in an environment with rapidly changing conditions, and who are able to adapt to the abrupt changes in the congestion window typical of TCP's Additive Increase Multiplicative Decrease (AIMD) congestion control. [STANDARDS-TRACK]
Forest Structure Classification in the North Columbia Mountains Using the Landsat TM Tasseled Cap Wetness Component

RÉSUMÉ L'objectif de cette étude est de déterminer le potentiel des images de télédétection satellitaire comme mesure prévisionnelle de la complexité de la structure de la forêt et de l'âge des peuplements. Des relations empiriques entre les paramètres structurels de la forêt et les données Landsat Thematic Mapper ont été analysées pour un échantillon de cèdres et pruches, et des peuplements d'épinettes d'Engelmann et de sapins de l'Ouest, près de Revelstoke, en Colombie britannique. Les méthodes utilisées pour mesurer la structure des peuplements forestiers sont présentées suivi d'une discussion sur l'analyse de corrélation entre les variables de terrain et la création d'un indice de complexité structurelle (SCI - structural complexity index) dérivé d'une analyse en composantes principales de plusieurs variables individuelles liées au peuplement. Les valeurs d'humidité TM dérivées de la transformation «tasseled cap» ont été corrélées fortement avec l'âge du peuplement et avec la complexité structurelle dans le cas des peuplements matures et âgés. On démontre que la distribution spatiale des valeurs d'humidité TM est reliée à la composition de la végétation et à la structure des communautés de climax à l'intérieur de deux sous-zones biogéoclimatiques majeures qui occupent la région. Les relations empiriques entre les valeurs d'humidité TM et le stade de succession récent ou avancé de la structure des peuplements se sont avérées variables. La composition hétérogène des espèces dans ces communautés peut expliquer les relations statistiques plus faibles. Les résultats démontrent l'utilité de l'application de la composante humidité de TM pour la classification de la structure forestière pour les peuplements forestiers matures et âgés et pour la cartographie des habitats à l'intérieur de cette zone d'étude.
Mobilizing Institutional Knowledge for International Projects

Multinational engineering consultants, contractors, and real estate developers work on projects in various countries, encountering many challenges that arise from cross-national differences. These projects frequently bring together diverse participants in an unfamiliar environment. In these situations, firms are exposed to different "institutions"—regulations, norms, and cognitive-cultural beliefs—that can increase misunderstandings, delays, and costs. Knowledge of these institutional elements is critical to create a project that is both locally sustainable and profitable for the firm. Departing from institutional theory and the knowledge-based view of the firm, we conduct exploratory research based on interviews from informants in 15 firms to identify the methods that multinational real estate developers, contractors, and engineers use to transfer and mobilize institutional knowledge for their global projects. We contribute to theory by adding to the developing literature that uses institutional theory to examine differences on global projects and by analyzing the specific methods firms use to transfer institutional knowledge internally, across projects and divisions. Ultimately, this research, combined with the work of others, can develop new processes for firms engaged in international projects to enhance their mobilization of institutional knowledge, and thereby improve the outcomes of international projects.
Future projection of mean river discharge climatology for the Chao Phraya River basin

: We projected future river discharge in the Chao Phraya River basin and evaluated the uncertainty in future climate projections by using different resolutions and ensemble experiments of the Atmospheric General Circulation Model of the Meteorological Research Institute (MRI-AGCM). We also obtained estimates of precipitation, evaporation, runoff, and river discharge under climate conditions projected for the late 21 st century. The results show that precipitation is projected to significantly increase in the future during April to August, excluding May. The projected river discharge at Nakhon Sawan located in the central region shows a peak in September, a delay of one month after the maximum monthly mean precipitation. The estimated reduction in river discharge for January and February was robust based on all members of the 60-km mesh MRI-AGCM ensembles changing in the same direction as that of the 20-km mesh MRI-AGCM. The uncertainty assessment conducted in this study could lead to increased robustness in projected changes in mean river discharge in the late 21 st century for this basin.
Two contrasting dust‐dominant periods over India observed from MODIS and CALIPSO data

Each year, prior to the onset of the Indian Summer Monsoon, the Gangetic Plains (GP), bounded by the high‐altitude Himalayan mountains, are strongly influenced by the transport of dust outbreaks originating in the northwestern desert in India (known as the Thar Desert). Dust particles constitute the bulk of the regional aerosol loading which peaks annually during the pre‐monsoon season. This paper integrates observations from space‐borne sensors, namely MODIS and CALIPSO, together with ground sunphotometer measurements, to infer dust loading in the pre‐monsoon aerosol build‐up over source and sink regions in northern India. Detailed aerosol characterization from the synergetic observational assessment suggests that the two pre‐monsoon seasons of 2007 and 2008 were strikingly contrasting in terms of the dust loading over both the Thar Desert and the GP. Further analysis of aerosol loading and optical properties, from the entire record of MODIS and sunphotometer observations, reveals that the 2007 pre‐monsoon season was an unusually weak dust‐laden period. Our findings suggest the plausible role of the immediately preceding excess winter monsoon rainfall in the suppressed dust activity during the 2007 pre‐monsoon season.
Active Learning for Named Entity Recognition in Clinical Text

Named entity recognition (NER) is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance. However, they often require large numbers of annotated samples, which are expensive to build with the use of domain experts in annotation. Active learning (AL), a sample selection approach that can be integrated with supervised ML, has shown the promising potential to minimize the annotation cost while maximizing the performance of ML-based models in various NLP tasks. However, very few studies have investigated AL for clinical NER in a real-life setting. In this dissertation research, I systematically studied AL in a clinical NER task to identify medical problems, treatments, and lab tests in clinical notes. Novel AL algorithms were developed to query the most informative and least costly sentences based on three properties: uncertainty, representativeness, and annotation time. I also developed the first AL-enabled annotation system for clinical NER. Using this system, I further conducted user studies to assess the performance of AL in real world annotation processes for building clinical NER systems. The initial user study shows that conventional AL methods with no consideration of annotation time did not always perform better than random sampling for different users. However, our newly developed AL algorithms with cost models for estimating annotation time were more promising in practice. To achieve an NER model with 0.70 in F-measure, simulated results show that the new AL method saved ~33.3% in estimated annotation time, compared to random sampling. In the user study, the new AL algorithm achieved better performance than random sampling and saved up to ~26.5% real annotation time for one of the users. To the best of our knowledge, this is the first study examining the practical AL systems for clinical NER. Our study demonstrates that AL has the potential to save annotation time and improve model quality for building ML-based NER systems, when novel querying algorithms are implemented. Our future work includes developing better querying algorithms and evaluating the system with larger number of users.