Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing a sequential cropping capability in the JULESvn5.2 land–surface model

Abstract. Sequential cropping (also known as multiple or double cropping) is a common feature, particularly for tropical regions, where the crop seasons are largely dictated by the main wet season such as the Asian summer monsoon (ASM). The ASM provides the water resources for crops grown for the whole year, thereby influencing crop production outside the ASM period. Land surface models (LSMs) typically simulate a single crop per year, however, in order to understand how sequential cropping influences demand for resources, we need to simulate all of the crops grown within a year in a seamless way. In this paper we implement sequential cropping in a branch of the Joint UK Land Environment Simulator (JULES) and demonstrate its use at Avignon, a site that uses the sequential cropping system and provides over 15-years of continuous flux observations which we use to evaluate JULES with sequential cropping. In order to implement the method in future regional simulations where there may be large variations in growing conditions, we apply the same method to four locations in the North Indian states of Uttar Pradesh and Bihar to simulate the rice--wheat rotation and compare model yields to observations at these locations. JULES is able to simulate sequential cropping at Avignon and the four India locations, representing both crops within one growing season in each of the crop rotations presented. At Avignon the maxima of LAI, above ground biomass and canopy height occur at approximately the correct time for both crops. The magnitudes of biomass, especially for winter wheat, are underestimated and the leaf area index is overestimated. The JULES fluxes are a good fit to observations (r-values greater than 0.7), either using grasses to represent crops or the crop model, implying that both approaches represent the surface coverage correctly. For the India simulations, JULES successfully reproduces observed yields for the eastern locations, however yields are under estimated for the western locations. This development is a step forward in the ability of JULES to simulate crops in tropical regions, where this cropping system is already prevalent, while also providing the opportunity to assess the potential for other regions to implement it as an adaptation to climate change.
Some new attacks upon security protocols

Many security protocols have appeared in the literature, with aims such as agreeing upon a cryptographic key, or achieving authentication. However, many of these have been shown to be flawed. In this paper we present a number of new attacks upon security protocols, and discuss ways in which we may avoid designing incorrect protocols in the future.
Information extraction for semi-structured documents

The number of unstructured or semi-structured documents produced in all types of organizations continues to increase rapidly. Cost-effective ways of finding the relevant ones and extracting useful information from them are increasingly important to a large number of enterprises for operational and decision-support applications. The approach discussed in this paper constitutes a suitable basis for building an effective solution to extracting information from semi-structured documents for two principal reasons. First, it provides an extensible architecture basis for: extracting structured information from semistructured documents; providing fast and accurate selective access to this information; performing selective dissemination of relevant documents depending on filtering criteria. Second, it is simple in terms of: the complexity of the algorithms used for structure recognition and document filtering; the number and size of data structures required to perform the three functions mentioned above; the amount and complexity of the metadata required to handle a given collection of documents. The work described here is part of the Dyade Médiation project, which aims to provide integrated software components for accessing heterogeneous data sources in Internet/Intranet environments.
Talking to Bots: Symbiotic Agency and the Case of Tay

In 2016, Microsoft launched Tay, an experimental artificial intelligence chat bot. Learning from interactions with Twitter users, Tay was shut down after one day because of its obscene and inflammatory tweets. This article uses the case of Tay to re-examine theories of agency. How did users view the personality and actions of an artificial intelligence chat bot when interacting with Tay on Twitter? Using phenomenological research methods and pragmatic approaches to agency, we look at what people said about Tay to study how they imagine and interact with emerging technologies and to show the limitations of our current theories of agency for describing communication in these settings. We show how different qualities of agency, different expectations for technologies, and different capacities for affordance emerge in the interactions between people and artificial intelligence. We argue that a perspective of “symbiotic agency”— informed by the imagined affordances of emerging technology—is required to really understand the collapse of Tay.
Brain death confirmation: comparison of computed tomographic angiography with nuclear medicine perfusion scan.

INTRODUCTION : Brain death is a difficult diagnosis to make, relying primarily on clinical examination. Ancillary tests are used when confounders exist. Nuclear medicine perfusion test (NMPT) is currently the preferred test for confirming brain death. Computed tomographic angiography (CTA) may be an alternative test to confirm brain death. It is readily available 24 hours a day at most level I trauma centers and is easy to perform. METHODS : Patients with a clinical examination consistent with brain death were selected from the intensive care unit at a 550-bed teaching hospital. The patients underwent NMPT followed immediately by CTA. Both studies were read by radiologists blinded to the results of the alternative study. Absence of brain perfusion confirmed brain death. Multiple independent variables were collected on each patient including demographics, core body temperature, apnea challenge, mechanism of injury, timelines, renal function pre- and posttesting, organ donation, and time to procurement. RESULTS : There were 25 patients enrolled in the study with multiple injury patterns. No false negative exams were identified on CTA when compared with NMPT. Three patients without flow on NMPT showed minimal flow on CTA. Each of these had open skull defects. Sensitivity of CTA was 0.86 and specificity was 1. There was no induced morbidity with regards to renal failure and organ donation. CONCLUSION : CTA is a quick and efficient test for brain death confirmation. CTA demonstrated no false negative studies. The resolution of CTA seems to have an increased sensitivity for cerebral blood flow. Further studies with larger sample sizes need to be performed.
Quantum cellular automata

The authors formulate a new paradigm for computing with cellular automata (CAS) composed of arrays of quantum devices-quantum cellular automata. Computing in such a paradigm is edge driven. Input, output, and power are delivered at the edge of the CA array only; no direct flow of information or energy to internal cells is required. Computing in this paradigm is also computing with the ground state. The architecture is so designed that the ground-state configuration of the array, subject to boundary conditions determined by the input, yields the computational result. The authors propose a specific realization of these ideas using two-electron cells composed of quantum dots. The charge density in the cell is very highly polarized (aligned) along one of the two cell axes, suggestive of a two-state CA. The polarization of one cell induces a polarization in a neighboring cell through the Coulomb interaction in a very non-linear fashion. Quantum cellular automata can perform useful computing. The authors show that AND gates, OR gates, and inverters can be constructed and interconnected.
On-Line Identification of PMSM Parameters: Model-Reference vs EKF

In this paper, a model-reference based on-line identification method is proposed to estimate PMSM parameters. The global stability of the augmented system is analyzed using the second method of Lyapunov and the singular perturbations theory. It is shown that this method may be applied with a decoupling control technique that improves convergence dynamics and overall system stability. This method is compared with an extended Kalman filter (EKF) based on-line identification approach and it is shown that in spite of its implementation complexity with respect to the proposed method, EKF does not give better results than the proposed method. The simulation results as well as the experimental ones, implemented on a non-salient pole PMSM, illustrate the validity of the analytic approach and confirm the same conclusions.
CLDA: Feature Selection for Text Categorization Based on Constrained LDA

Feature selection is a necessary process before pattern classification, machine learning and data mining. Now feature selection is facing challenge in high dimension space, such as text categorization in information retrieval. Linear discriminant analysis (LDA) is an excellent dimensionality reduction method which transforms the original data into low-dimensional feature space. However, it changes the original physical features and makes features uninterpretable, which motivates us to select but not transform features by LDA idea of preserving structure information of between-class and within-class for text categorization. In the paper, a new approach of feature selection based on constrained LDA (CLDA) is proposed, which models feature selection as a search problem in subspace and finds optimal solution subject to some restrictions. Further, CLDA optimization problem is transformed into a process of scoring and sorting of features. Experiments on 20 newsgroups and Reuters-21578 show that CLDA is consistently better than information gain and chi2-test with lower computational complexity.
Model-Free Robust Optimal Feedback Mechanisms of Biological Motor Control

Sensorimotor tasks that humans perform are often affected by different sources of uncertainty. Nevertheless, the central nervous system (CNS) can gracefully coordinate our movements. Most learning frameworks rely on the internal model principle, which requires a precise internal representation in the CNS to predict the outcomes of our motor commands. However, learning a perfect internal model in a complex environment over a short period of time is a nontrivial problem. Indeed, achieving proficient motor skills may require years of training for some difficult tasks. Internal models alone may not be adequate to explain the motor adaptation behavior during the early phase of learning. Recent studies investigating the active regulation of motor variability, the presence of suboptimal inference, and model-free learning have challenged some of the traditional viewpoints on the sensorimotor learning mechanism. As a result, it may be necessary to develop a computational framework that can account for these new phenomena. Here, we develop a novel theory of motor learning, based on model-free adaptive optimal control, which can bypass some of the difficulties in existing theories. This new theory is based on our recently developed adaptive dynamic programming (ADP) and robust ADP (RADP) methods and is especially useful for accounting for motor learning behavior when an internal model is inaccurate or unavailable. Our preliminary computational results are in line with experimental observations reported in the literature and can account for some phenomena that are inexplicable using existing models.
An Improved Landweber Method for Restoration of Aero-Optically Degraded Images

Aero-optic effects cause distortions, including blurring, vibration, deformation and spatial shifting, of the objects in the image obtained by the infra-red sensor. Contributions of this paper are in the following two aspects. First, the correctness of the theoretical point spread function (PSF) representing the aero-optic effects, which had been derived in our previous research, is validated experimentally. Second, in order to restore the aero-optically degraded images, an improved Landweber iteration method is proposed, where, instead of being fixed, the relaxation factor is updated adaptively at each iteration. Experiments have been carried out and results demonstrate that the proposed method introduces improved restoration results with better convergence.
Sports Program Boundary Detection

In the recent years, consumer devices that can record broadcast video have become prevalent. Such devices rely on the program guide information about a program start time and end time for recording. However, sports broadcasts can run over the specified time sometimes. In this paper, we propose a framework based on an audio classification framework to correctly detect the end of a sport broadcast so as to enable complete recording of the game. Our experimental results show that the proposed algorithm can detect sports program boundaries with a high accuracy
Combining crowd-generated media and personal data: semi-supervised learning for context recognition

The growing ubiquity of sensors in mobile phones has opened many opportunities for personal daily activity sensing. Most context recognition systems require a cumbersome preparation by collecting and manually annotating training examples. Recently, mining online crowd-generated repositories for free annotated training data has been proposed to build context models. A crowd-generated dataset can capture a large variety both in terms of class number and in intra-class diversity, but may not cover all user-specific contexts. Thus, performance is often significantly worse than that of user-centric training. In this work, we exploit for the first time the combination of both crowd-generated audio dataset available in the web and unlabeled audio data obtained from users' mobile phones. We use a semi-supervised Gaussian mixture model to combine labeled data from the crowd-generated database and unlabeled personal recording data. Hereby we refine generic knowledge with data from the user to train a personalized model. This technique has been tested on 7 users on mobile phones with a total data of 14 days and up to 9 context classes. Preliminary results show that a semi-supervised model can improve the recognition accuracy up to 21%.
A Fuzzy Extension to the OWL 2 RL Ontology Language

Fuzzy extensions to Description Logics (DLs) have gained considerable attention the last decade. So far most works on fuzzy DLs have focused on either very expressive languages, like fuzzy OWL and OWL 2, or on highly inexpressive ones, like fuzzy OWL 2 QL and fuzzy OWL 2 EL. To the best of our knowledge a fuzzy extension to the language OWL 2 RL has not been thoroughly studied so far. This language is very relevant since it combines both adequate expressive power as well as efficient reasoning algorithms which can be realised using rule-based (Datalog) technologies. In contrast to previous fuzzy extensions, a fuzzy extension of OWL 2 RL is not a straightforward task for the following reason. The main motivation of OWL 2 RL is that its axioms can be equivalently represented as Datalog rules. Hence, to achieve our goal we need to investigate which OWL 2 RL axioms when interpreted under the fuzzy setting can be transformed to equivalent fuzzy Datalog rules. We show that this is not, in general, possible for all axioms but we show that this “issue” can to a large extent be alleviated. Moreover, we have performed an experimental evaluation with many well-known ontologies which showed that such axioms are not used so often in practice.
Impact of Delayed and Quantized Channel State Information at the Transmitter

We study the effects of delayed and quantized channel state information at the transmitter (CSIT) on the system performance. Using the average rate as a performance measure, we quantify the effect of these imperfections, acting individually as well as in tandem. Numerical results as well as approximations confirm that while few bits are sufficient to come close to the capacity, even small delays result in rather large losses in the average rate.
The abstract of critical discourse analysis of radicalism labeling by BNPT to Islamic site

The development of radicalism issues is begun by a radical group movement and its spread in social media is labeled as a radical element by , The Agency of National Counter Terrorism (BNPT). This research issues radicalism through the language because there is an element of the radical language becoming criteria of radical in social media. Pursuant to factual logical data, views from readers, this research aims at; 1) describing the criteria of the language use labelled radical by BNPT in Islamic pages; 2) investigating the ideology of radicalism views in Islamic pages; 3) describing how BNPT views Islamic pages; 4) finding the relevant result toward the discourse analysis learning in universities. The approach used in this study is the Critical Discourse Study approach belonging to descriptive qualitative. This study is based on the theory of Critical Discourse Analysis (CDA) as the main theories and supported by the use of Social Semiotic Theory proposed by Halliday to analyze criteria of radical language. Besides, this study is also based on the theory of ideology by Raymond William and Louis Althusser. To collect the data needed, this study employed observation and documentation techniques. The data gathered were then analyzed by using formal and informal methods. Then, they were categorized, classified, identified, labeled, and the data described. Based on results of the data analysis, it shows the use of the symbol or label criteria radical language, a linguistic and ideological overview of features on the site indicated radical and BNPT ’s view to that site. By examining from the perspective of macro and microstructure in the text, there are three topics the issue of jihad, demonstrations, takfirin . Besides, the use of microstructure including semantic syntactic, stylistic, rhetorical is the domain in terms of microstructure. In addition, there are micro syntactic and semantic aspects, stylistic, and rhetorical aspects that domain the results.
Comparative Evaluation of Individual and Coupled Inductor Arrangements for Input Filters of PV Inverter Systems

Photovoltaic systems (PV) of higher power are connected to the grid through three-phase inverters via output filters which are designed to limit Electromagnetic Interference (EMI), in order to comply with international standards. With the purpose of reducing the volume of this converter, this paper evaluates 3 configurations of bridge legs and output magnetic components and identifies the most compact options for a system of 10kVA. A single bridge leg and two interleaved bridge legs with coupled or uncoupled inductors are considered in the comparison. Switching frequency and total silicon area are fixed and the volume of the passive components and the heatsink are evaluated as well as the system efficiency. The analysis developed in this paper show that the configuration with interleaved bridge legs and coupled inductors has a total volume close to 70% when compared to the configuration with interleaved bridge legs and uncoupled inductors, but it has a similar total volume when compared to the configuration with a single bridge leg. Although it is reported in the literature that systems with coupled inductors usually have a lower volume, the case at hand has the output filters designed to comply with EMI standards and it will be shown that, like this, the volume reduction of magnetic components provided by coupled inductors is compensated by the increase on the volume of capacitors.
Grazing Incidence Small Angle X ‐ ray Scattering ( GISAXS ) Study of Mesoporous Silica Thin Films on Metal Substrates

Mesoporous silica (MS) thin films contain ordered arrays of nanometer‐sized pores and are of interest for many applications. Prior work using GISAXS, a scattering/diffraction technique that allows determination of pore spacing and degree of ordering and alignment, found that for MS templated by the block co‐polymer, Pluronic P123, the type of metal substrate used impacts the size, spacing, ordering, and alignment of the pores. It is expected that different block co‐polymer templates will similarly impact the pore spacing, ordering and alignment in unique ways. We report here an analysis of GISAXS data from MS thin films on a range of metals templated by the block co‐polymers, Pluronic P123 and Pluronic L92. Introduction A material is said to be mesoporous if it has pores with diameters from 2‐50 nm [12]. Mesoporous materials, in general, have large surface areas, and this gives them great potential in many chemical applications [16]. One mesoporous material, in particular, that has sparked considerable interest is mesoporous silica (MS). In the early 1990's, researchers at the Mobil Research and Development Corporation developed a method called Surfactant Templating. This method was able to produce mesoporous silica in which the pores were uniform in size, evenly spaced, and well aligned with respect to each other [2]. Furthermore, the researchers found that by adjusting the template with which the MS was synthesized, it was possible to align the pores into set patterns such as hexagonal and spherical pore orientations. In the mid‐90's, scientists at the University of California, Santa Barbara reported that using block co‐polymers as a liquid crystal template, rather than the ionic surfactants used by the Mobil research group, allows for a wider variety of both pore shapes and sizes in MS [1]. This new method, of which SBA‐15 and SBA‐16 are the most common examples, became the standard for preparing MS with large pore sizes. With the ability to both predict and manipulate the arrangement of the pores, research interest in MS
2 Overview of DPG 2 . 1 A Generalized Minimum Residual Method

We introduce two robust DPG methods for transient convection-diffusion problems. Once a variational formulation is selected, the choice of test norm critically influences the quality of a particular DPG method. It is desirable that a test norm produce convergence of the solution in a norm equivalent to L while producing optimal test functions that can be accurately computed and maintaining good conditioning of the optimal test function solve on highly adaptive meshes. Two such robust norms are introduced and proven to guarantee close to L convergence of the primary solution variable. Numerical experiments demonstrate robust convergence of the two methods.
Application of Virtualisation Techniques at a University Grid Center

Computing clusters at universities are often shared between many different user groups, having their own requirements concerning computing infrastructure, e.g. the operating system (OS), software packages, access policies and different grid middlewares. The integration of local computing and storage resources into the grid of a specific user group is realised by portal machines, providing different services. In the current implementation of the Worldwide LHC Grid and the CDF grid middleware, these services require dedicated operating systems and should be installed on different machines for stability reasons. Virtualisation of these services on one high-capacity machine eases maintenance of the systems and reduces the hardware overhead especially for smaller clusters. This approach of hardware consolidation is not restricted to the grid infrastructure and may therefore be applied to other even simpler services. This paper describes the process of hardware consolidation at a typical university grid centre. A discussion of different virtualisation techniques is also included and benchmarks show that Xen is an optimal candidate.