Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECT OF FLOW REGIME AND TURBIDITY ON PERIPHYTON IN A LABORATORY SYSTEM by CLAYTON LAMAR BIRKETT ( Under the direction of

This study was to design and develop a laboratory system for studying flow regime and turbidity interactions on periphyton development under three turbidity regimes. The flume was configured to create areas of distinct flow regime by using multiple roughness conditions and an in-channel weir. The one dimensional hydraulic model HEC-RAS was useful for modeling channel velocities and related properties, although the abrupt channel geometry and narrow channels appeared to cause some discrepancies in depth predictions. The results suggest that turbidity should be kept between 100 mg/l and 200 mg/l for periphyton growth, tending to confirm the 250 mg/l limit in the literature. Mean velocity was a fairly good predictor of live biomass (chlorophyll a) and filament length. The turbulent RMS velocity was the better predictor of dead biomass (pheophytin). Chlorophyll a concentration at the 100 mg/l sediment concentration was greatest, most likely due to periphyton compensation to turbidity-induced shading. INDEX WORDS: Periphyton, Chlorophyll, Turbidity, Flow Regime, HEC-RAS THE EFFECT OF FLOW REGIME AND TURBIDITY ON PERIPHYTON IN A LABORATORY SYSTEM
Native Language Influence During Second Language Acquisition : A Large-Scale Learner Corpus Analysis

Learners’ interlanguage is affected by their native language (L1) during second language (L2) acquisition. Current literature focuses on narrow samples, necessitating a large-scale study of the topic. The present study uses a corpus of over 133,000 texts, composed by nearly 38,000 learners of English as foreign language, representing seven different L1s, and all L2 proficiency levels. The effects of the structural relationship between learners’ L1 and the target L2 were examined. Overall, there was significant variation, as both structural similarities and differences could either facilitate acquisition, hinder it, or have no significant effect.
The Distribution of Soil Testate Amoebae under Winter Snow Cover at the Plot-scale Level in Arctic Tundra (Qeqertarsuaq/Disko Island, West Greenland)

Summary. Understanding the spatial distribution of soil protozoa under the snow cover is important for estimation of ecosystem responses to climate change and interpretation of results of fi eld experiments. This work explores spatial patterns of soil testate amoebae under the snow cover at the plot scale (the range of metres) in arctic tundra (Qeqertarsuaq/Disko Island, West Greenland). To explain spatial patterns in abundance, species diversity and assemblage composition of testate amoebae, we measured microtopography, snow depth and substrate density. The results indicate that the abundance of active testate amoebae under the snow cover was quite low. The empty shell assemblage was characterised by the presence of linear spatial trends in the species composition across the site, whereas no patterns were detected within the plot. The distribution of the abundance and the species diversity were unstructured. The linear trends in the species composition corresponded to the site microtopography and were controlled by the topography-related soil moisture. Snow depth also affected the linear trends presumably by controlling soil temperatures. Overall, the results suggest that population processes do not generate spatial patterns in protozoan assemblages at the plot scale so that protozoan distribution can be considered random at macroscopically homogeneous plots.
A MEMORY EFFICIENT INCREMENTAL GRADIENT METHOD FOR REGULARIZED MINIMIZATION

Abstract. In this paper, we propose a new incremental gradient methodfor solving a regularized minimization problem whose objective is thesum of msmooth functions and a (possibly nonsmooth) convex function.This method uses an adaptive stepsize. Recently proposed incrementalgradient methods for a regularized minimization problem need O(mn)storage, where n is the number of variables. This is the drawback ofthem. But, the proposed new incremental gradient method requires onlyO(n) storage. 1. IntroductionIn this paper, we consider the regularized minimization problem whose formis(1) min x∈ℜ n F λ (x) := f(x) +λP(x),where λ > 0, P : ℜ n → (−∞,∞] is a proper, convex, lower semicontinuous(lsc) function [20], and(2) f(x) :=X mi=1 f i (x),where each function f i is real-valued and smooth (i.e., continuously diﬀeren-tiable) on an open subset of ℜ n containing domP = {x | P(x) < ∞}. The minimization problem (1) we consider arises in many applications suchas (supervised) learning [7, 12, 27], regression [17, 23], neural network training[11, 21, 29], and data mining/classiﬁcation [5, 15, 22, 28]. For the l
Framing Childhood: Representations of Children in Gunnar Lundh’s Photo Agency Archive

Based on Gunnar Lundh’s photographs from the period 1920-1960, this article aims to discuss how a visualisation of children and childhood in cultural history collections can be addressed. This period is known as the time when the Swedish welfare state and society took shape, a period when the conditions for children in society changed in a number of ways. Lundh’s photographs are therefore viewed as cultural expressions of an era of cultural, societal and political change in which photographs of children came to play a particularly important role. Some of Lundh’s pictures have been reproduced in works about the constructive period of the Swedish welfare state and have thereby had an important role in narrating the story of the welfare society. In this way, Lundh’s photographs of children must be understood in the specific context of visual representations of children and childhood from this time period. In the many pictures of children in Lundh’s collection, the children play, are dressed up in fine clothes and national costumes, visit the library, pick flowers, play along the shore, etc. The children are depicted both active and passive, innocent, childish and pure. In that sense, the photographs follow a genre-specific way to portray children which was typical at the time and still is. In the article, I argue that an understanding and a specific way of seeing and portraying children and childhood became institutionalised during this period. However, in this institutionalisation process of images of childhood, Lundh’s pictures of children seem to reproduce and enhance this “pictorial vocabulary” in many ways that appear natural to childhood. Hörnfeldt, Helena “Framing Childhood: Representations of Children in Gunnar Lundh’s Photo Agency Archive. ”, Culture Unbound, Volume 12, issue 1, 2020: 65– 89. Published by Linköping University Electronic Press: http://www.cultureunbound. ep.liu. se
Environmental Value Orientation and Environmental Impact Perception of Visitors to Khao Yai National Park

The purposes of this study were to examine environmental value orientation and perceptions of the environmental impacts of domestic visitors in Khao Yai National Park (KYNP) across three groups of activities: campers, hikers and bird-watchers. A total of 628 questionnaires were distributed to participants in these three major activities. The results showed that visitors enjoyed a high level of environmental value. The majority of campers, hikers, and bird-watchers were ecocentrists (valuing nature for its own sake). Proportionately, there were more ecocentrists among the bird-watchers compared to the campers and hikers, while there were more anthropocentric hikers than campers and bird-watchers. For impact perception, more than 30 percent of visitors indicated that visitor activities did not cause environmental impacts. The majority of visitors rated the severity of impact in KYNP at the moderate level. Visitors who engaged in different types of recreational activities perceived impacts differently. Overall, bird-watchers perceived impacts at a higher level of severity than either campers or hikers. For management recommendations, KYNP needs to seriously consider more effective environmental education programs to create a positive environmental attitude and improve the ecological impact knowledge of visitors that is a primary factor underlying environmentally friendly behavior.
Reliable Visual Exploration System with Fault Tolerance Structure

Reliability of visual tracking and mapping is a challenging problem in robotics research, and it limits the promotion of vision-based mobile robot applications to a great extent. In this paper, we propose to improve the reliability of visual exploration in terms of its fault tolerance. Three modules are involved in our visual exploration system: visual localization and mapping, active controller and termination condition. High maintainability of mapping is obtained by the submap-based visual mapping module, persistent driving is achieved by a semantic segmentation based active controller, and robustness of re-localization is guaranteed by a novel completeness evaluation method in the termination condition. All the modules are integrated tightly for maintaining mapping and improving visual tracking. The system is verified with simulations and real world experiments, and all the solutions to fault tolerance are verified to overcome the failure conditions of visual tracking and mapping.
Semi-Supervised Deep Learning Approach for Transportation Mode Identification Using GPS Trajectory Data

Identification of travelers’ transportation modes is a fundamental step for various problems that arise in the domain of transportation such as travel demand analysis, transport planning, and traffic management. In this paper, we aim to identify travelers’ transportation modes purely based on their GPS trajectories. First, a segmentation process is developed to partition a user's trip into GPS segments with only one transportation mode. A majority of studies have proposed mode inference models based on hand-crafted features, which might be vulnerable to traffic and environmental conditions. Furthermore, the classification task in almost all models have been performed in a supervised fashion while a large amount of unlabeled GPS trajectories has remained unused. Accordingly, we propose a deep SEmi-Supervised Convolutional Autoencoder (SECA) architecture that can not only automatically extract relevant features from GPS segments but also exploit useful information in unlabeled data. The SECA integrates a convolutional-deconvolutional autoencoder and a convolutional neural network into a unified framework to concurrently perform supervised and unsupervised learning. The two components are simultaneously trained using both labeled and unlabeled GPS segments, which have already been converted into an efficient representation for the convolutional operation. An optimum schedule for varying the balancing parameters between reconstruction and classification errors are also implemented. The performance of the proposed SECA model, trip segmentation, the method for converting a raw trajectory into a new representation, the hyperparameter schedule, and the model configuration are evaluated by comparing to several baselines and alternatives for various amounts of labeled and unlabeled data. Our experimental results demonstrate the superiority of the proposed model over the state-of-the-art semi-supervised and supervised methods with respect to metrics such as accuracy and F-measure.
Understanding Complex Multi-sentence Entity seeking Questions

We present the novel task of understanding multi-sentence entity-seeking questions (MSEQs) i.e, questions that may be expressed in multiple sentences, and that expect one or more entities as an answer. We formulate the problem of understanding MSEQs as a semantic labeling task over an open representation that makes minimal assumptions about schema or ontology specific semantic vocabulary. At the core of our model, we use a BiDiLSTM (bi-directional LSTM) CRF and to overcome the challenges of operating with low training data, we supplement it by using hand-designed features, as well as hard and soft constraints spanning multiple sentences. We find that this results in a 6-7pt gain over a vanilla BiDiLSTM CRF. We demonstrate the strengths of our work using the novel task of answering real-world entity-seeking questions from the tourism domain. The use of our labels helps answer 53% more questions with 42 % more accuracy as compared to baselines.
Cross-Entropy as a Metric for the Robustness of Drone Swarms

Due to their growing number and increasing autonomy, drones and drone swarms are equipped with sophisticated algorithms that help them achieve mission objectives. Such algorithms vary in their quality such that their comparison requires a metric that would allow for their correct assessment. The novelty of this paper lies in analysing, defining and applying the construct of cross-entropy, known from thermodynamics and information theory, to swarms. It can be used as a synthetic measure of the robustness of algorithms that can control swarms in the case of obstacles and unforeseen problems. Based on this, robustness may be an important aspect of the overall quality. This paper presents the necessary formalisation and applies it to a few examples, based on generalised unexpected behaviour and the results of collision avoidance algorithms used to react to obstacles.
Sightings, strandings and Irukandji Syndrome caused by envenomations of the large, rarely observed jellyfish; Keesingia gigas Gershwin, 2014 (Cnidaria: Cubozoa: Carybdeida: Alatinidae) in north-western Australia

Beach strandings of 31 Keesingia gigas Gershwin, 2014, occurred in Exmouth Gulf, north-western Australia, between 16 and 25 March 2016, with 17 strandings recorded in just two days. Between 28 March and 31 May 2017 there were another 54 reports of K. gigas, many of multiple individuals, mostly on the Ningaloo coast west of Exmouth. These events provided an opportunity to examine this large but rarely observed jellyfish, as the only previous specimen collected was the holotype, off Shark Bay in 2012. Of 19 specimens collected and/or photographed on the beach in 2016, overall medusa length ranged from 190 to 345 mm, except for two 80 mm individuals. All but one of the smallest lacked tentacles, consistent with the original description of the species, photographs and field observations recorded in this study. The tentacles observed on the smallest animal examined may represent ontogenetic variability. Clusters of nematocysts were observed on the velarial margin of the bell. Three confirmed envenomations of adult people in 2016 did not result in them developing symptoms of Irukandji syndrome, however among six confirmed envenomations in 2017, two stings to adults resulted in some systemic Irukandji syndrome symptoms. In 2016, most sightings of K. gigas were in Exmouth Gulf, while in 2017 almost all were on the ocean side of North West Cape, indicating distribution was not solely restricted to Exmouth Gulf. Prevailing winds in the five days leading up to strandings in 2016 also suggest the jellyfish had been transported from the ocean north of Exmouth and not from within Exmouth Gulf. Similarly in 2017, prevailing winds and waves were consistent with currents moving jellyfish from north to south, with the time course of observations beginning in the northern part of Ningaloo in March and finishing in the southern section in May. All known sightings of K. gigas have been made in the March to May period in five separate years. Public awareness campaigns by the Shire of Exmouth in 2016 and Department of Biodiversity, Conservation and Attractions in 2017 were successful in raising awareness of the potential threat to swimmers and beach users and also proved effective in obtaining reports of the distribution of K. gigas.
Stable isotope probing analysis of ammonia oxidizer interactions

The response of natural microbial communities to environmental change can be assessed by determining DNAor RNA-targeted changes in relative abundance of 16S rRNA gene sequences, using fingerprinting techniques such as denaturing gradient gel electrophoresis (DNA-DGGE and RNA-DGGE, respectively), or by stable isotope probing (SIP) of 16S rRNA genes following incubation with a C-labeled substrate (DNA-SIP-DGGE). The sensitivities of these three approaches were compared during batch growth of communities containing twoor three Nitrosospira pure or enriched cultures, with different tolerances to high ammonia concentration. Cultures were supplied with low, intermediate or high initial ammonia concentrations and with C-labeled carbon dioxide. DNA-SIP-DGGE provided the most direct evidence for growth and was most sensitive, with changes in DGGE profiles evident before changes in DNAand RNA-DGGE profiles and before detectable increases in nitrite and nitrate production. RNA-DGGE provided intermediate sensitivity. In addition, the three molecular methods were used to follow growth of individual strains within communities. In general, changes in relative activities of individual strains within communities could be predicted from monoculture growth characteristics. Ammonia-tolerant Nitrosospira cluster 3b strains dominated mixed communities at all ammonia concentrations and ammonia-sensitive strains were outcompeted at intermediate ammonia concentration. However, coexistence of ammonia-tolerant and ammonia-sensitive strains occurred at the lowest ammonia concentration, and, under some conditions, strains inhibited at high ammonia in monoculture were active at high ammonia in mixed cultures, where they coexisted with ammonia-tolerant strains. The results therefore demonstrate the sensitivity of SIP for detection of activity of organisms with relatively low yield and activity and its ability to follow changes in the structure of interacting microbial communities. at U N IV E R S IT Y O F A B E R D E E N on M arch 7, 2010 em . sm . rg D ow nladed fom
First Toba supereruption revival

Little has been known about the earliest Toba eruptive episodes that created the largest-known caldera complex of Quaternary age. Here we report evidence for the eastward dispersal of the oldest Toba tuff in South China Sea sediments to 2500 km away from the source. The tephra deposits occur below the Brunhes-Matuyama geomagnetic boundary (778 ka) and slightly above the Australasian microtektite layer (793 ka). Calibrated by astronomically tuned oxygen isotope stratigraphy, the middle Pleistocene Toba eruption occurred during the deglaciation at 788 ′ 2.2 ka, according to the tephra occurrence between marine isotope stages 20 and 19. This refined age is in good agreement with the 4 0 Ar/ 3 9 Ar date of 800 ′ 20 ka for the Toba tephra (layer D) from Ocean Drilling Program (ODP) Site 758, but significantly younger than the commonly cited Ar/Ar age of 840 ′ 30 ka. The eruption expelled at least 800-1000 km 3 dense-rock-equivalent of rhyolitic magma on the basis of the widespread tephra-fall deposit in the basins of the Indian Ocean and the South China Sea. In spite of its exceptional magnitude, the timing of this major eruption does not indicate a causal linkage between this event and a long-term global climatic deterioration.
X-ray image denoising with directional support value transform

Under the support vector machine framework, the support value analysis-based image fusion has been studied, where the salient features of the original images are represented by their support values. The support value transform (SVT)-based image fusion approach have demonstrated some advantages over the existing methods in multisource image fusion. In this paper, the directional support value transform (DSVT) is applied to the denoising of some standard images embedded in white noise and the X-ray images. This directional transform is not norm-preserving and, therefore, the variance of the noisy support values will depend on the scales. And then we use the hard-thresholding rule for estimating the unknown support values in different scales and the thresholding is scale-dependent. The peak signal noise ratio (PSNR) is used as an "objective" measure of performance, and our own visual capabilities are used to identify artifacts whose effects may not be well-quantified by the PSNR value. The experimental results demonstrate that simple thresholding of the support values in the proposed method is very competitive with techniques based on wavelets, including thresholding of decimated or undecimated wavelet transforms.
Current Control of a Six-Phase Induction Machine Drive Based on Discrete-Time Sliding Mode with Time Delay Estimation

This paper proposes a robust nonlinear current controller that deals with the problem of the stator current control of a six-phase induction motor drive. The current control is performed by using a state-space representation of the system, explicitly considering the unmeasurable states, uncertainties and external disturbances. To estimate these latter effectively, a time delay estimation technique is used. The proposed control architecture consists of inner and outer loops. The inner current control loop is based on a robust discrete-time sliding mode controller combined with a time delay estimation method. As said before, the objective of the time delay estimation is to reconstruct the unmeasurable states and uncertainties, while the sliding mode aims is to suppress the estimation error, to ensure robustness and finite-time convergence of the stator currents to their desired references. The outer loop is based on a proportional-integral controller to control the speed. The stability of the current closed-loop system is proven by establishing sufficient conditions on the switching gains. Experimental work has been conducted to verify the performance and the effectiveness of the proposed robust control scheme for a six-phase induction motor drive. The results obtained have shown that the proposed method allows good performances in terms of current tracking, in their corresponding planes.
Life Time Evolution of Wireless Sensor Network in Presence of Energy Hole at Sink

: Wireless sensor networks play vital role in data gathering. They often work in hostile environments where nodes are not having any energy refilling. Therefore the lifetimes of network and energy consumption are very important. The aim of any technique is to increase lifetime of the network with optimizations. The rationale behind this is that the network has sensor nodes that are resource constrained. In this paper we proposed a model used to determine the effects of energy hole and estimate network lifetime in presence of energy hole at sink. Energy hole is characterized and studied in order to find its effect on the lifetime of the network. We used NS2 simulations in order to evaluate our work. The experimental results revealed that the proposed model is useful to determine the life time of WSN.
Linking Mechanism of Inward FDI and Bilateral Exchange Rate

This research study examines the impact of the bilateral exchange rate (BEXR) on FDI inflow into the South Asian countries, i.e. Pakistan, India, Bangladesh, Sri Lanka, Nepal, Bhutan, Afghanistan, and the Maldives. Panel data technique is used to investigate the results while using the data from 2004 to 2016. Moreover, static panel data technique cannot be used to provide robust results as the causality of variables challenge the model. To resolve the problem dynamic panel model (GMM) is used. The investigated results show a mixed trend. OLS Model showed that BEXR is negatively related (when significant) to FDI inflow. Similarly, the static panel model showed that BEXR has a negative relationship with FDI inflow, but the relationship is not significant. However, the results estimated by Dynamic panel model (GMM) are different from the previous models. It showed that BEXR has a positive relationship with FDI inflow. The positive relationship of BEXR with FDI inflow is in line with the theories that strong currency discourages FDI into the country while weak currency motivates FDI into the country. The exchange rate in emerging economies (South Asia) is rather lower that can be availed by MNEs (foreign investors) to invest in these countries. Similarly, the study can help the policy makers of these countries to enhance FDI into the country as FDI boosts the economy of the country.