Miracle-dz/UniFAR-FTUs huggingface dataset:
New low cost sorbents for Cr(VI) – batch and column experiments

The use of agricultural byproducts and industrial biowaste materials has been shown to be an attractive technique for removing Cr(VI) from contaminated waste waters. In this study, used brewers draff, peat moss, sawdust, grape stalks and husks were investigated as novel biosorbents for Cr(VI). The material was tested in two different modifications. The material was dried, cut and sieved and part of it was subjected to acid (2 M H2SO4) and alkali (0.5 M NaOH) pre-treatments to remove starch, proteins and sugars. Fourier transform infrared rays analysis on solid phase (FTIR-ATR) was used to determine the main functional groups that might control the metal uptake. Batch experiments were performed at different pH values (3, 4.5, 6) and at various initial concentration of Cr(VI) (25-250 mg L -1 ). Two equilibrium empirical models, Langmuir and Freundlich, were used to describe Cr(VI) adsorption. In order to identify possible reduction processes, ion exchange separation on the AG1-X8 resin was used to separate the anionic Cr(VI) and the reduced cationic Cr(III) from the aqueous phase after biosorption. As expected, Cr(VI) removal was pH-dependent and fitted well both the Langmuir and Freundlich isotherm models. The ion exchange separation showed that Cr(VI) reduction had occurred in the solution during biosorption. The efficiency of draff as a biosorbent was comparable (or even higher) to highly organic materials (e.g., composted peat) showing its potential application for Cr(VI) decontamination.
Research on Power Short-term Prediction of the Photovoltaic System Based on Grey Relational Analysis and Quantum Particle Swarm Optimization

Output power of Photovoltaic generation system is influenced by temperature, humidity, solar radiation intensity and so on. The effects of three kinds of external climate conditions, including temperature, humidity, solar radiation intensity, on photovoltaic output power were anal sized in detail in this paper, and then similar days for photovoltaic power prediction were selected based on grey relational analysis. The quantum particle swarm optimization method for optimizing kernel parameters of support vector machine was immediately introduced. In line with the data of similar days and optimization parameters of kernel function, a new power short-term prediction method of the photovoltaic system based on grey relational analysis and quantum particle swarm optimization was put up in this paper. According to the data of photovoltaic output power and meteorological monitoring data of Wulan photovoltaic power station, the method mentioned is likely verified. Instances proved that this new power short-term prediction method has great advantages in terms of speed, accuracy and stability. Keywords-photovoltaic power prediction; grey relational analysis; battery characteristics; quantum particle swarm optimization; support vector machine; wulan photovoltaic power station
Discovering User's Trends and Routines from Location Based Social Networks

Location data is a powerful source of information to discover user’s trends and routines. A suitable identification of the user context can be exploited to provide automatically services adapted to the user preferences. In this paper, we define a Dynamic Bayesian Network model and propose a method that processes location annotated data in order to train the model. Finally, our model enables us to predict future location contexts from the user patterns. A case study evaluates the proposal using real-world data of a location-based social network.
Causal Nexus between Billing Efficiency and Economic Growth in India: An Analysis Using Vector Autoregression

Energy being a major factor of production plays a pivotal role in inducing a sustained and high economic growth of an economy. This paper attempts to examine the Vector Autoregression (VAR) based Granger causality between billing efficiency and growth rate of per capita Gross Domestic Product (GDP) of India using annual time series data for the period 1970-71 to 2014-15. The conventional Augmented Dicky-Fuller and Phillips-Perron tests reveal that both the series are non-stationary and individually integrated of order one. Johansen-Juselius cointegration approach finds no evidence on the long-run equilibrium association between these variables. However, the VAR - based Granger causality approach reveals unidirectional causality running from billing efficiency to economic growth without any feedback effect. As regards policy implication, implementation of both the short term and long term measures in improving billing efficiency, through the enhancement of commercial and operational efficiency in electricity distribution sector will undoubtedly aid in achieving sustained and high economic growth in India.
A STRESS-FREE APPROACH TO TEFL

The teaching of English in Indonesia has been marked with the frequent changesin the curriculum. However, those changes do not imply whatsoever any changesin the way teachers deliver lessons in a moment-to-moment classroom teaching.We seem to be too much preoccupied with new concepts and perhaps approach toteaching English but fail to formulate how a certain concept can be translated intoclassroom methods and techniques. This paper seeks to shed a light on how a synthesisof various approaches in language learning can be achieved to provide favorablelearning atmosphere for students and more importantly how different theorieson language learning can be transformed into an operational method andtechniques in the classroom.
What do your eyes say? Bridging eye movements to consumer behavior ¿Qué dicen sus ojos? Conectando los movimientos oculares hacia el comportamiento del consumidor

Eye tracking (ET) is a technique that has been progressively employed to study the influence of visual stimuli on attentional processes and consumer behavior. The goals of the present theoretical article are fourfold and are based on an extensive literature revision,. First, a brief historical review of ET methodology is introduced, presenting the evolution of ET techniques from the ancient proto-eye trackers to the “fresh” state-of-theart eye ET devices. Second, the basics of ET are clarified through a simplified technical and mathematical explanation. Third, the triad eye movement-attention-consumer behavior is made clear, grounded on attention, interest, desire, and action (AIDA) theoretical model. Fourth, the most used oculometrics in marketing studies are explained and distinguished The present article addresses a number of technical and methodological issues by discussing challenges involved in ET systems and giving some guidelines for those who intend to apply ET to infer cognitive and emotional processes.
MODELLING THE DYNAMICS OF WEED MANAGEMENT TECHNOLOGIES

An appropriate economic framework for valuing the benefits of weed management technologies is to treat weeds as a renewable resource stock problem. Consequently, the weed seed bank is defined as a renewable resource that changes through time due to management and seasonal conditions. The goal of decision-makers is to manage this (negative) resource so as to maximise returns over some pre-specified period of time. A modelling framework is presented for evaluating the biological and economic effects of weed management. The framework includes population dynamics, water balance, crop growth, pasture growth and crop/pasture rotation models for measuring the physical interactions between weeds and the environment. These models link in with numerical optimal control, dynamic programming and stochastic dynamic programming models for determination of optimal decision rules and measuring economic impact over time of policy scenarios.
Analysis And Simulation Of Low Profile Planar Inverted - F Antenna Design For WLAN Operation In Portable Devices

: This paper presents a compact planar inverted–F antenna (PIFA) design for WLAN operation in portable devices. The proposed design has size of 8 x 21 mm and provides peak directive gain of 5.78dBi with the peak return loss of -33.89dB and input impedance of 50. 28Ω. It covers a 10dB return loss bandwidth of 410MHz (2.37GHz – 2.789GHz). Its VSWR varies from 1.96 to 1.93 within the antenna return loss bandwidth. As the dimension of the proposed antenna is very small, the antenna is promising to be embedded within the different portable devices employing Wi–Fi applications. This paper includes the return loss as a function of frequency with varying the different parameters, VSWR, input resistance, radiation pattern and current distribution of the proposed antenna.
Stochastic volatility driven by large shocks

This paper presents a new model of stochastic volatility which allows for infrequent shifts in the mean of volatility, known as structural breaks. These are endogenously driven from large innovations in stock returns arriving in the market. The model has a number of interesting properties. Among them, it can allow for shifts in volatility which are of stochastic timing and magnitude. This model can be used to distinguish permanent shifts in volatility coming from large pieces of news arriving in the market, from ordinary volatility shocks.
A Jack of all Trades? Solving stochastic mixed-integer nonlinear constraint programs

Natural gas is one of the most important energy sources in Germany and Europe. In recent years, political regulations have led to a strict separation of gas trading and gas transport, thereby assigning a central role in energy politics to the transportation and distribution of gas. These newly imposed political requirements influenced the technical processes of gas transport in such a way that the complex task of planning and operating gas networks has become even more intricate. Mathematically, the combination of discrete decisions on the configuration of a gas transport network, the nonlinear equations describing the physics of gas, and the uncertainty in demand and supply yield large-scale and highly complex stochastic mixed-integer nonlinear optimization problems. The Matheon project "Optimization of Gas Transport" takes the key role of making available the necessary core technology to solve the mathematical optimization problems which model the topology planning and the operation of gas networks. An important aspect of the academic impact is the free availability of our framework. As a result of several years of research and development, it is now possible to download a complete state-of-the-art framework for mixed-integer linear and nonlinear programming in source code at http://scip.zib. de
Enriching Neural Models with Targeted Features for Dementia Detection

Alzheimers disease is an irreversible brain disease that slowly destroys memory skills andthinking skills leading to the need for full-time care. Early detection of Alzheimer’s dis-ease is fundamental to slow down the progress of the disease. In this work we are developing Natural Language Processing techniques to detect linguistic characteristics of patients suffering Alzheimer’s Disease and related Dementias. We are proposing a neural model based on a CNN-LSTM architecture that is able to take in consideration both long language samples and hand-crafted linguistic features to distinguish between dementia affected and healthy patients. We are exploring the effects of the introduction of an attention mechanism on both our model and the actual state of the art. Our approach is able to set a new state-of-the art on the DementiaBank dataset achieving an F1 Score of 0.929 in the Dementia patients classification Supplementary material include code to run the experiments.
Frequency of endomycorrhizal infection in grazed and ungrazed blue grama plants.

Highlight: The frequency of mycorrhizal infection in blue grama roots was determined from two criteria: (1) occurrence of any mycorrhizal element, and (2) occurrence of fungal vesicles. No significant differences were observed with respect to grazing using the first frequency criteria. However, roots of previously grazed plants had significantly higher frequencies of vesicles than those collected from exclosures. Frequency of vesicles was found to increase linearly with increase in rooting depth of blue grama. Significant grazing effects on the frequency of vesicles were observed primarily in the first sample depth, 0-10 cm.
Mir-BFT: High-Throughput BFT for Blockchains

This paper presents Mir-BFT (or, simply, Mir), a robust Byzantine fault-tolerant (BFT) total order broadcast protocol aimed at maximizing throughput on wide-area networks (WANs), targeting permissioned and Proof-of-Stake permissionless blockchains. We show that Mir achieves unprecedented throughput on WANs without sacrificing latency, robustness to malicious behavior, or even performance in clusters. Our evaluation shows that Mir orders more than 60000 signed Bitcoin-sized transactions per second on a widely distributed 100 nodes, 1 Gbps WAN setup, while preventing a range of attacks including request duplication performance attacks. To achieve this, Mir relies on a novel protocol mechanism that allows a set of leaders to propose request batches independently, in parallel, while rotating the assignment of a partitioned request hash space to leaders. Several optimizations boost Mir throughput even further, including partial replication through a novel abstraction we call light total order (LTO) broadcast. Perhaps most importantly, Mir relies on proven BFT protocol constructs, which simplifies reasoning about Mir correctness. Specifically, Mir is a generalization of the celebrated and scrutinized PBFT protocol. In a nutshell, Mir follows PBFT ``safety-wise'', with changes needed to accommodate novel features restricted to PBFT liveness.
Meta Learning via Learned Loss

Typically, loss functions, regularization mechanisms and other important aspects of training parametric models are chosen heuristically from a limited set of options. In this paper, we take the first step towards automating this process, with the view of producing models which train faster and more robustly. Concretely, we present a meta-learning method for learning parametric loss functions that can generalize across different tasks and model architectures. We develop a pipeline for “meta-training” such loss functions, targeted at maximizing the performance of the model trained under them. The loss landscape produced by our learned losses significantly improves upon the original task-specific losses in both supervised and reinforcement learning tasks. Furthermore, we show that our meta-learning framework is flexible enough to incorporate additional information at meta-train time. This information shapes the learned loss function such that the environment does not need to provide this information during meta-test time. We make our code available at https://sites.google. com/view/mlthree
Cytogenetic analyses of two endemic fish species from the São Francisco River basin: Conorhynchus conirostris and Lophiosilurus alexandri (Siluriformes)

Two Siluriformes species endemic to the Sao Francisco River basin were characterized by conventional and differential cytogenetic analyses involving C-banding, Ag-nucleolar organizer region (NOR) and chromomycin A3 (CMA3) staining, and FISH (fluorescent in situ hybridization) with 18S and 5S rDNA probes. Conorhynchus conirostris presents a higher diploid number (2n = 60) than those detected in Pimelodidae representatives, whereas Lophiosilurus alexandri, with a karyotype of 2n = 54 chromosomes, presents a chromosomal constitution similar to that found in the family Pseudopimelodidae. Plesiomorphic characteristics such as single NORs at terminal positions are found in both species, as revealed by CMA3 and silver nitrate staining, and FISH with a 18S rDNA probe. C-banding evidenced centromeric and telomeric heterochromatic blocks distributed over most of the chromosomes with a conspicuous heterochromatin segment in a pair of submetacentric chromosomes in L. alexandri. Such karyotype data, if compared to the cytogenetic pattern of other Siluriformes species, can be partially related to their degree of endemism, favorable to the occurrence and fixation of chromosomal rearrangements. The present study in representatives from these two Siluriformes families from the Sao Francisco River contributes to a better understanding of the karyotype evolution in species of this important order of Neotropical fishes.
Building the British Sign Language Corpus

This paper presents an overview of the British Sign Language Corpus Project – the first endeavor ever to create a machine-readable digital corpus of British Sign Language (BSL) collected from deaf signers across the United Kingdom. In the field of sign language studies, it represents a unique combination of methodology from variationist sociolinguistics and corpus linguistics. Unlike previous large-scale sign language sociolinguistic projects, the dataset is being annotated and tagged using ELAN software, given metadata descriptions, and the video data has been made accessible, with long-term efforts to make the dataset searchable on-line. This means, however, that participants must consent to having the video data of their sign language use made public. This puts at risk the authenticity of the linguistic data collected, as signers may monitor their production more carefully than usual. We discuss our attempt to minimise this problem by creating a dual-access archive.
Two modes of recognition: algebra, coalgebra, and languages

The aim of the paper is to build a connection between two approaches towards categorical language theory: the coalgebraic and algebraic language theory for monads. For a pair of monads modelling the branching and the linear type we defined regular maps that generalize regular languages known in classical non-deterministic automata theory. These maps are behaviours of certain automata (i.e. they possess a coalgebraic nature), yet they arise from Eilenberg-Moore algebras and their homomorphisms (by exploiting duality between the category of Eilenberg-Moore algebras and saturated coalgebras). Given some additional assumptions, we show that regular maps form a certain subcategory of the Kleisli category for the monad which is the composition of the branching and linear type. Moreover, we state a Kleene-like theorem characterising the regular morphisms category in terms of the smallest subcategory closed under certain operations. Additionally, whenever the branching type monad is taken to be the powerset monad, we show that regular maps are described as maps recognized by certain functors whose codomains are categories with all finite hom-sets. We instantiate our framework on classical non-deterministic automata, tree automata, fuzzy automata and weighted automata.
MULT . GPU PROG . Parallel 3 D Fast Wavelet Transform comparison on CPUs and GPUs

Correspondence: gbernabe@ditec.um. es Computing Engineering, University of Murcia,Campus de Espinardo, 30071 Murcia, Spain Full list of author information is available at the end of the article Abstract We present in this paper several implementations of the 3D Fast Wavelet Transform (3DFWT) on multicore CPUs and manycore GPUs. On the GPU side, we focus on CUDA and OpenCL programming to develop methods for an efficient mapping on manycores. On multicore CPUs, OpenMP and Pthreads are used as counterparts to maximize parallelism, and renowned techniques like tiling and blocking are exploited to optimize the use of memory. We evaluate these proposals and make a comparison between a new Fermi Tesla C2050 and an Intel Core 2 Quad Q6700. Speedups of the CUDA version are the best results, improving the execution times on CPU, ranging from 5.3x to 7.4x for different image sizes, and up to 81 times faster when communications are neglected. Meanwhile, OpenCL obtains solid gains which range from 2x factors on small frame sizes to 3x factors on larger ones.
Characteristics of Isotropically Conductive Adhesive (ICA) Filled with Carbon Nanotubes (CNTs) and Low-Melting-Point Alloy Fillers

A new class of isotropic conductive adhesive (ICA) using a carbon nanotubes (CNTs) and a low-melting-point alloy (LMPA) fillers has been developed. We investigated the fundamental materials characteristics including curing behavior and temperature-dependant viscous property of ICA. In addition, the morphology of conduction paths in each ICA was investigated using X-ray inspection systems and an optical microscope. Mechanical and electrical characteristics of formulated ICAs were determined and compared with those of three kinds of conventional ICAs filled with Ag flakes. The CNT-filled solderable ICA formed good metallurgical interconnection between upper and corresponding lower electrode. In addition, the results indicated that the CNT-filled ICA exhibit lower electrical resistance and higher mechanical strength, as compared with those of conventional ICAs.
HL Tau Disk in HCO+ (3–2) and (1–0) with ALMA: Gas Density, Temperature, Gap, and One-arm Spiral

We present our observational results of the 1.1 mm continuum and the HCO+ (3–2) line in HL Tau at angular resolutions of 0. ″1 obtained with Atacama Large Millimeter/submillimeter Array and our data analysis of the 2.9 and 1.1 mm continuum and the HCO+ (3–2) and (1–0) lines of the HL Tau disk. The Keplerian rotation of the HL Tau disk is well resolved in the HCO+ (3–2) emission, and the stellar mass is estimated to be 2.1 ± 0.2 M☉ with a disk inclination angle of 47°. The radial profiles of the HCO+ column density and excitation temperature are measured with the LTE analysis of the two transitions of the HCO+ emission. An HCO+ gas gap at a radius of 30 au, where the column density drops by a factor of 4–8, is found in the HCO+ column density profile, coincident with the dust gap traced by the continuum emission. No other clear HCO+ gas gap is seen. This HCO+ gas gap can be opened by a planet with mass of 0.5–0.8 MJ, which is comparable to the planet mass adopted in numerical simulations to form the dust gap at the same radius in the HL Tau disk. In addition to the disk component, a one-arm spiral with a length of ∼3″ (520 au) stretching out from the inner disk is observed in the HCO+ (3–2) emission. The observed velocity structures along the spiral suggest an infalling and rotating gas stream toward the inner disk.