Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes to flow and turbulence caused by different concentrations of fish in a circular tank

ABSTRACT The effects of juvenile Atlantic salmon (Salmo salar) on flow and turbulence in a circular tank were investigated. Three fish sizes were studied (37.5 g, 82.5 g and 218 g) with between 268,050 and 318,000 fish in a 15 m diameter by 4 m deep tank (mean stocking densities of 15.3 kg m–3, 35.6 kg m–3, and 79.4 kg m–3). Flow in the enclosed tank was driven by the inflow from the water supply system and a degassing system. Velocities were measured using acoustic Doppler velocimetry with and without fish present. Dissolved oxygen was also measured, and the turbulent transport of dissolved oxygen calculated from eddy correlation. The average water velocity was reduced by 15% at low and medium stocking densities, and 57% at high stocking density. Turbulent kinetic energy, turbulence intensity, and turbulence dissipation rates were higher with fish than without. Fish altered the distributions of mean velocity, turbulence and oxygen, and increased the turbulent transport of oxygen. Vertical distributions of turbulence were consistent with echo-sounder derived fish distributions.
Modelling wastewater aeration system and high-speed turbo blower for energy efficiency improvements

In efforts to improve wastewater treatment plants’ energy efficiency, optimization of aeration process is often a point of interest due to its high energy intensity. Improvements in aeration blower technologies and process control strategies offer prospects for cutting down aeration energy consumption. Alternative to traditional blower technologies is the high-speed turbo blower, which along with improved energy efficiency offers many fringe benefits, which makes it a worthy candidate for blower replacement projects. With the high-speed technology, blower’s electrical complexity increases, creating some special considerations for the component manufacturers. This study attempts to characterize typical operation of a high-speed turbo blower in wastewater aeration process, in order to identify challenges and possibilities for energy efficiency improvements on equipment level. Study includes literature review on diffused aeration systems structure and control strategies, blower technologies and associated variable frequency drives and electric motors. A model of the diffused aeration system and high-speed turbo blowers of the Hermanninsaari wastewater treatment plant is developed for assessing the typical operating patterns and loadings of high-speed turbo blowers. Simulation results highlighted the challenges for energy efficiency optimization of highspeed turbo blower’s electrical equipment, whereas minimizing the backpressure through valve control optimization algorithms, could offer large savings for relatively small reductions in the backpressure. For systems operating larger blower groups, blower operating strategy has more possibilities for energy optimization.
Origin of low-tropospheric potential vorticity in Mediterranean cyclones

Abstract. Mediterranean cyclones are extratropical cyclones, typically of smaller size and weaker intensity than other cyclones that develop over the main open ocean storm tracks. Nevertheless, Mediterranean cyclones can attain high intensities, even comparable to the ones of tropical cyclones, and thus cause large socioeconomic impacts in the densely populated coasts of the region. After cyclogenesis takes place, a large variety of processes are involved in the cyclone’s development, contributing with positive and negative potential vorticity (PV) changes to the lower-tropospheric PV anomalies in the cyclone center. Although the diabatic processes that produce these PV anomalies in Mediterranean cyclones are known, it is still an open question whether they occur locally within the cyclone itself or remotely in the environment (e.g., near high orography) with a subsequent transport of high-PV air into the cyclone center. This study introduces a Lagrangian method to determine the origin of the lower-tropospheric PV anomaly, which is applied climatologically to ERA5 reanalysis and to 12 monthly simulations, performed with the integrated forecasting system (IFS) model. We define and quantify so-called “cyclonic” and “environmental” PV and find that the main part of the lower-tropospheric PV anomaly (60 %) is produced within the cyclone, shortly prior (−12 h) to the cyclones' mature stage. Nevertheless, in 19.5 % of the cyclones the environmental PV production near the mountains surrounding the Mediterranean Basin plays a significant role in forming the low-tropospheric PV anomaly and therefore in determining the intensity of these cyclones. The analysis of PV tendencies from the IFS simulations reveals that the major PV production inside the cyclone is typically due to convection and microphysics, whereas convection and turbulent momentum tendencies cause most of the positive PV changes in the environment.
Computers & Graphics How neuroticism and locus of control a ff ect user performance in high-dimensional data visualization

The impact of individual di ff erences, such as personality traits, on user performance and human behaviors has been studied in several fields of human-computer interaction, with a growing interest in information visualization. Although most visualizations are still designed with a universal approach, great strides have been made toward the development of user-adaptive visualizations catered to the user’s personality. We analyze how personality a ff ects user interaction with high-dimensional visualizations. Specifi-cally, we explore the impact of neuroticism (including its facets) and locus of control in user performance and confidence. Results suggest that neurotic individuals are faster with the scatterplot matrix, while individuals with an internal locus are more confident when using the parallel coordinates plot. In addition, results indicate that the facets of neuroticism have significant - and distinct from neuroticism - impact on user performance and confidence, pointing toward the need to analyze traits, such as neuroticism, at a lower level.
Involvement of Thalamocortical Networks in Patients With Poststroke Thalamic Aphasia

Background and Objective Theories assume that thalamic stroke may cause aphasia because of dysfunction in connected cortical networks. This takes into account that brain functions are organized in distributed networks, and in turn, localized damage may result in a network disorder such as thalamic aphasia. With this study, we investigate whether the integration of the thalamus into specific thalamocortical networks underlies symptoms after thalamic stroke. We hypothesize that thalamic lesions in patients with language impairments are functionally connected to cortical networks for language and cognition. Methods We combined nonparametric lesion mapping methods in a retrospective cohort of patients with acute or subacute first-ever thalamic stroke. A relationship between lesion location and language impairments was assessed using nonparametric voxel-based lesion-symptom mapping. This method reveals regions more frequently damaged in patients with compared with those without a symptom of interest. To test whether these symptoms are linked to a common thalamocortical network, we additionally performed lesion-network-symptom mapping. This method uses normative connectome data from resting-state fMRI of healthy participants (n = 65) for functional connectivity analyses, with lesion sites serving as seeds. Resulting lesion-dependent network connectivity of patients with language impairments was compared with those with motor and sensory deficits as baseline. Results A total of 101 patients (mean [SD] age 64.1 [14.6] years, 57 left, 42 right, and 2 bilateral lesions) were included in the study. Voxel-based lesion-symptom mapping showed an association of language impairments with damage to left mediodorsal thalamic nucleus lesions. Lesion-network-symptom mapping revealed that language compared with sensory deficits were associated with higher normative lesion-dependent network connectivity to left frontotemporal language networks and bilateral prefrontal, insulo-opercular, midline cingular, and parietal domain-general networks. Lesions related to motor and sensory deficits showed higher lesion-dependent network connectivity within the sensorimotor network spanning prefrontal, precentral, and postcentral cortices. Discussion Thalamic aphasia relates to lesions in the left mediodorsal thalamic nucleus and to functionally connected left cortical language and bilateral cortical networks for cognitive control. This suggests that dysfunction in thalamocortical networks contributes to thalamic aphasia. We propose that inefficient integration between otherwise undamaged domain-general and language networks may cause thalamic aphasia.
International Journal of Electrical and Computer Engineering (IJECE)

Received Dec 28, 2021 Revised Jul 13, 2022 Accepted Aug 10, 2022 The reversible logic gates are used to improve the power dissipation in modern computer applications. The floating-point numbers with reversible features are added advantage to performing complex algorithms with highperformance computations. This manuscript implements an efficient reversible floating-point arithmetic (RFPA) unit, and its performance metrics are realized in detail. The RFP adder/subtractor (A/S), RFP multiplier, and RFP divider units are designed as a part of the RFP arithmetic unit. The RFPA unit is designed by considering basic reversible gates. The mantissa part of the RFP multiplier is created using a 24x24 Wallace tree multiplier. In contrast, the reciprocal unit of the RFP divider is designed using Newton Raphson’s method. The RFPA unit and its submodules are executed in parallel by utilizing one clock cycle individually. The RFPA unit and its submodules are synthesized separately on the Vivado IDE environment and obtained the implementation results on Artix-7 field programmable gate array (FPGA). The RFPA unit utilizes only 18.44% slice look-up tables (LUTs) by consuming the 0.891 W total power on Artix-7 FPGA. The RFPA unit sub-models are compared with existing approaches with better performance metrics and chip resource utilization improvements.
Task Modeling: Approximating Multitask Predictions for Cross-Task Transfer

We study the problem of learning a target task when data samples from several 1 auxiliary source tasks are available. Examples of this problem appear in multitask 2 learning, where several tasks are combined jointly, and weak supervision, where 3 multiple programmatic labels are generated for each sample. Because of task data’s 4 heterogeneity, negative interference is a critical challenge for solving this problem. 5 Previous works have measured first-order task affinity as an effective metric, yet 6 it becomes less accurate for approximating higher-order transfers. We propose a 7 procedure called task modeling to model first-and higher-order transfers. This 8 procedure samples subsets of source tasks and estimates surrogate functions to 9 approximate multitask predictions. We show theoretical and empirical results that 10 task models can be estimated in nearly-linear time in the number of tasks and 11 accurately approximate multitask predictions. Thus, the target task’s performance 12 can be optimized using task models to select source tasks. We validate this approach 13 on various datasets and performance metrics. Our method increases accuracy up to 14 3.6% over existing methods on five text classification tasks with noisy supervision 15 sources. Additionally, task modeling can be applied to group robustness and 16 fairness metrics. Ablation studies show that task models can accurately predict 17 whether or not a set of up to four source tasks transfer positively to the target task. 18
Fishy : Layerwise Fisher Approximation for Higher-order Neural Network Optimization

We introduce Fishy , a local approximation of the Fisher information matrix at each layer for natural gradient descent training of deep neural networks. The true Fisher approximation for deep networks involves sampling labels from the model’s predictive distribution at the output layer and performing a full backward pass – Fishy deﬁnes a Bregman exponential family distribution at each layer, performing the sampling locally. Local sampling allows for model parallelism when forming the preconditioner, removing the need for the extra backward pass. We demonstrate our approach through the Shampoo optimizer, replacing its preconditioner gradients with our locally sampled gradients. Our training results on deep autoencoder and VGG16 image classiﬁcation models indicate the efﬁcacy of our construction.
Estimating Efforts for Various Activities in Agile Software Development: An Empirical Study

Effort estimation is an important practice in agile software development. The agile community believes that developers’ estimates get more accurate over time due to the cumulative effect of learning from short and frequent feedback. However, there is no empirical evidence of an improvement in estimation accuracy over time, nor have prior studies examined effort estimation in different development activities, which are associated with substantial costs. This study fills the knowledge gap in the field of software estimation in agile software development by investigating estimations across time and different development activities based on data collected from a large agile project. This study investigated effort estimation in various development activities, including feature development, bug fixing, and refactoring in agile software development. The results indicate that estimation of agile development does not improve over time, as claimed in the literature. Our data also indicate that no difference exists in the magnitude of estimation errors between feature tasks and bug-fixing/refactoring tasks, while bug-fixing and refactoring tasks are overestimated more frequently than feature tasks. This study also contributes to our knowledge about overestimation and underestimation patterns in agile software development.
A Two-Step Method for Ensuring Printed Document Integrity using Crossing Number Distances

Nowadays, with the use of photo-editing software being mainstream, document integrity verification has become crucial. As we have seen during the pandemic, most administrative documents are printed and then scanned before being transmitted, making these documents noisy. Indeed, a printed and scanned document undergoes geometric transformations, as well as the addition of black spots, not to mention a decrease in color intensity. The relevant features of an original document, which will be matched against a query document, are stored to be used as a template. We propose a 2-step method that compares a template with a query document to ensure that the query document has not been tampered with. Our method first reverts geometric transformations the document underwent, and then extracts the crossing numbers in that image. A Euclidean distance based matching method is applied to the two sets of crossing numbers, and abnormally distant point groups are flagged as potentially modified. A second step in our method is then applied to analyze the statistical properties of these distance values, to ensure that the document has not been altered. Our results when we apply our method to a database containing administrative documents and tampered versions of these documents - all of which underwent a print and scan process - show the validity of our considerations.
Fire and Smoke Detection using Fully Supervised Training Methods and Search by Quad-Tree

—Wildﬁres are one of the most destructive and uncon-trollable natural disasters faced by man-kind. The ﬁre-ﬁghting combat teams can greatly beneﬁt from a reliable source of information about the different aspects within a ﬁre scene. By locating, in real time, the current position of the ﬁre fronts, a better ﬁghting strategy can be developed to help the efﬁciency of the operations. It is also critical, the detection of the early ﬁre ignitions to take action as soon as possible. This work proposes an original deep learning method for ﬁre and smoke detection using aerial images of wildﬁres. We trained both a full image classiﬁer and a segmentation network in order to detect the presence of ﬁre/smoke and to localize the regions of the images containing said phenomenon. Along side the detection component, we used an innovative Quad-Tree algorithm to increase the precision of the detections, processing the images into smaller patches. The proposed system was able to produce segmentations with a high level of precision and detail, achieving an Avg. IoU of 0.88 for ﬁre and 0.83 for the smoke class on a test aerial image dataset. The system proved to be highly capable of being used on a real ﬁre scenario.
Characterization of offline analysis of particulate matter with FIGAERO-CIMS

Abstract. Measurements of the molecular composition of organic aerosol (OA) constituents improve our understanding of sources, formation processes, and physicochemical properties of OA. One instrument providing such data at a time resolution of minutes to hours is the chemical ionization time-of-flight mass spectrometer with filter inlet for gases and aerosols (FIGAERO-CIMS). The technique collects particles on a filter, which are subsequently desorbed, and the evaporated molecules are ionized and analyzed in the mass spectrometer. However, long-term measurements using this technique and/or field deployments at several sites simultaneously require substantial human and financial resources. The analysis of filter samples collected outside the instrument (offline) may provide a more cost-efficient alternative and makes this technology available for the large number of particle filter samples collected routinely at many different sites globally. Filter-based offline use of the FIGAERO-CIMS limits this method, albeit to particle-phase analyses, which is likely at a reduced time resolution compared to online deployments. Here we present the application and assessment of offline FIGAERO-CIMS, using Teflon and quartz fiber filter samples that were collected in autumn 2018 in urban Beijing. We demonstrate the feasibility of the offline application with a “sandwich” sample preparation for the over 900 identified organic compounds with (1) high signal-to-noise ratios, (2) high repeatability, and (3) linear signal response to the filter loadings. Comparable overall signals were observed between the quartz fiber and Teflon filters for 12 and 24 h samples but with larger signals for semi-volatile compounds for the quartz fiber filters, likely due to adsorption artifacts. We also compare desorption profile (thermogram) shapes for the two filter materials. Thermograms are used to derive volatility qualitatively based on the desorption temperature at which the maximum signal intensity of a compound is observed (Tmax⁡). While we find that Tmax⁡ can be determined with high repeatability (±5.7 ∘C) from the duplicate tests for one filter type, we observe considerable differences in Tmax⁡ between the quartz and Teflon filters, warranting further investigation into the thermal desorption characteristics of different filter types. Overall, this study provides a basis for expanding OA molecular characterization by FIGAERO-CIMS to situations where and when deployment of the instrument itself is not possible.
The global atmospheric energy transport analysed by a wavelength-based scale separation

Abstract. The atmosphere transports energy polewards by circulation cells and eddies. To the present day, there has been a knowledge gap regarding the preferred spatial scales and physical mechanisms of eddy energy transport. To fill the gap, we separate the meridional atmospheric energy transport in the ERA5 reanalysis by spatial scales and into quasi-stationary and transient flow patterns and latent and dry components. Baroclinic instability is the major instability mechanism in the transient synoptic scales and is responsible for forming cyclones, anticyclones, and small-scale Rossby waves. At the planetary scales, circulation patterns are often induced by other mechanisms such as flow interaction with orography and land–sea heating contrasts. However, a separation between circulation patterns at the synoptic and planetary scales has yet to be established. We find that both baroclinically induced and transient energy transport is predominantly associated with eddies at wavelengths between 2000 and 8000 km. The maxima in both types of transport occur at wavelengths around 5000 km, in good agreement with linear baroclinic theory. Since these results are independent of latitude, we adapt the scale separation of the energy transport to be based on the wavelength instead of the previously used wavenumber. We define the synoptic transport by the wavelength band between 2000 and 8000 km. We analyse the annual and seasonal mean in the energy transport components and their inter-annual variability. The scale-separated transport components are fairly similar in both hemispheres. Transport by synoptic waves is the largest contributor to extra-tropical energy and moisture transport, mainly of a transient character, and is influenced little by seasonality. In contrast, transport by planetary waves depends highly on the season and has two distinct characteristics. (1) In the extra-tropical winter, planetary waves are important due to a large transport of dry energy. This planetary transport features the largest inter-annual variability of all components and is mainly quasi-stationary in the Northern Hemisphere but transient in its southern counterpart. (2) In the sub-tropical summer, quasi-stationary planetary waves are the most important transport component, mainly due to moisture transport, presumably associated with monsoons. In contrast to transport by planetary and synoptic waves, only a negligible amount of energy is transported by mesoscale eddies (< 2000 km).
Multi-Domain Task Completion Dialog Challenge II at DSTC9

The paper provides an overview of the “Multi-Domain Task-Completion Dialog Challenge II” track at the 9th Dialog System Technology Challenge ( DSTC 9). Two tasks are introduced in this track. One is end-to-end multi-domain task-completion, which focuses on building end-to-end task completion dialog systems. The other is cross-lingual dialog state tracking, which seeks to build a tracker for the target language using the source language resources. We describe the task settings, baselines, evaluation methods, and submission results for both tasks.
On the A ˛ -spectral Radius of Graphs Without Large Matchings

Let G be an n -vertex graph. A matching in G is a set of independent edges, i.e., no two edges in the set are adjacent in G . The matching number is the maximal size of a matching in G . Nikiforov (Appl Anal Discrete Math 11(1):81–107, 2017) proposed the A α -matrix of a graph G , as follows: where D ( G ) and A ( G ) are the diagonal degree matrix and adjacency matrix of G , respectively. In this contribution, we establish some A α -spectral conditions to guarantee that there do not exist large matchings in a graph G , recovering the previous results and obtaining similar results for a wide variety of spectral conditions from the A α -matrix. Our main tools are the Berge–Tutte formula and the double leading eigenvectors.