Miracle-dz/UniFAR-FTUs huggingface dataset:
PERFORMANCE OF HYDRAULIC RAM BUILT WITH DIFFERENT VOLUMES OF AIR CHAMBER

1Irrigation Engineering Laboratory, Federal Rural University of Amazônia (UFRA), e-mail: veniciusoliveira@hotmail.com 2 Professor of Agronomy, Federal Rural University of Amazônia (UFRA), e-mail: raimundo.lima@ufra.edu. br 3 Technological and Exact Sciences Center, Western Paraná State University (UNIOESTE), e-mail: wendelmoreira21@outlook.com 4 Technological and Exact Sciences Center, Western Paraná State University (UNIOESTE), e-mail: juciley2709@gmail.com 5 Irrigation Engineering Laboratory, Federal Rural University of Amazônia (UFRA), e-mail: cledsonagro2014@gmail.com 6 Irrigation Engineering Laboratory, Federal Rural University of Amazônia (UFRA), e-mail: jrodriguesufra@gmail.com
Folia Linguistica

This study focuses on nominal pluralization in Sign Language of the Netherlands (NGT). The aim is to offer a comprehensive description of nominal pluralization processes in the language, based on both corpus data and elicited data, taking into account potential phonological restrictions. The results reveal that NGT nouns can undergo several pluralization processes, the main ones being simple reduplication (i.e., repeating the noun sign at one location) and sideward reduplication (i.e., repeating the noun sign while moving the hand sideward). The choice of pluralization process depends on phonological properties of the base noun: (i) nouns that are body-anchored or involve a complex movement undergo simple reduplication; (ii) nouns articulated at the lateral side of the signing space undergo sideward reduplication; (iii) nouns articulated on the midsagittal plane can undergo both simple and sideward reduplication. Strikingly, the data show considerable variation, and all types of nouns can be zero-marked, that is, plural marking on the noun is not obligatory. The results further suggest that all nouns can undergo at least one type of reduplication. Thus, while phonological properties of the base noun influence the type of reduplication, they do not block reduplication altogether. Plural reduplication in NGT is therefore less constrained than has been reported for other sign languages, where certain noun types cannot undergo reduplication. This shows that reduplication – despite being iconically motivated – is subject to languagespecific grammatical constraints.
The Escherichia coli s E -dependent extracytoplasmic stress response is controlled by the regulated proteolysis of an anti- s factor

The activity of the stress-responsive s factor, s E , is induced by the extracytoplasmic accumulation of misfolded or unfolded protein. The inner membrane protein RseA is the central regulatory molecule in this signal transduction cascade and acts as a s E -specific anti- s factor. Here we show that s E activity is primarily determined by the ratio of RseA to s E . RseA is rapidly degraded in response to extracytoplasmic stress, leading to an increase in the free pool of s E and initiation of the stress response. We present evidence that the putative inner membrane serine protease, DegS, is responsible for this regulated degradation of RseA.
Enveloping skewfields of the nilpotent positive part and the Borel subsuperalgebra of osp(1,2n)

We study an analogue of the Gelfand-Kirillov property for some Lie superalgebras. More precisely, we consider in the classical simple orthosymplectic Lie superalgebra osp (1 , 2 n ) of dimension n 2 +3 n the positive nilpotent subsuperalgebra n + of dimension n 2 + n and the solvable Borel subsuperalgebra b + of dimension n 2 +2 n . We prove that the enveloping algebras U ( n + ) and U ( b + ) are rationally equivalent to some super-analogues of Weyl algebras over polynomial superalgebras.
Extraction and analysis of the structure of a drainage network from Digital Elevation Models

A new algorithm, for the removal of Digital Elevation Models errors especially developed for depressions and flat areas, is presented then applied to extract drainage network. The algorithm uses neighbourhood techniques as well as iterative spatial techniques that depends on a threshold : the maximum area of depression zone. This method was used to delineate catchment boundaries, to extract drainage network and to examine the geomorphology of twelve basins having their outlet in the Mediterranean sea in the Languedoc-Roussillon region southern France. The sensitivity of the model was analysed then the fractal geometry was used to analyse morphometric and scaling properties. The use of fractals allows to point out self-similarity in the structure of channel networks and to define new catchment shape indexes useful for comparing catchments.
(eHsp70) levels with mortality in adult patients with septic shock, as well as the association between eHsp70 levels and the APACHE II and SOFA scores, and the cytokines inflam‐

The aim of the present study was to determine the association between extracellular heat shock protein (eHsp70) levels with mortality in adult patients with septic shock, as well as the association between eHsp70 levels and the APACHE II and SOFA scores, and the cytokines inflam‐ matory response. The present study was an observational, longitudinal, prospective, cohort study. Adult patients with septic shock admitted to the intensive care unit (ICU) were included in the study; the eHsp70 levels were measured in sera by ELISA, and the APACHE II and SOFA scores were determined upon admission and every two days until death or discharge for improvement. The levels of pro‐inflammatory cytokines were measured at baseline and at discharge. A total of 90 patients were included, 53 males and 37 females. In total, 50% (n=45) patients succumbed to the disease. Upon admission to the ICU, the eHsp70 levels (mean ± SE) were higher in the deceased patients (1,963±461.9) compared with those in the survivors (1,499±482.0, P=0.02). ROC curve analysis for predicting mortality revealed that the eHsp70 concentration during admission to the ICU exhibited an area under the curve of 0.63, despite Kaplan‐Meier analysis, which revealed that the two higher quartiles of Hsp70 levels predicted an early mortality. Higher APACHE II and SOFA scores, as well as interleukin (IL)‐6 (2,229±687 vs. 1,116±441, P=0.03), IL‐8 (995±310 vs. 206±88, P=0.005) and IL‐18 (1,482±314 vs. 664±150, P=0.001) levels were found in the deceased patients. Thus, the present study demonstrates that high levels of eHsp70, and high APACHE II and SOFA scores, as well as a higher pro‐inflammatory response is associated with mortality. eHsp70 may thus prove to be a marker of severity in adult patients with septic shock.
A Thematic Analysis of Organisational Ambidexterity in Family Businesses Get the Girl a Brewery , Now !

This study examines organisational ambidexterity in the context of a family firm, where socioemotional wealth is used as a framework for capturing dynamics inherent to family businesses. The purpose of the study is to explore the relationship between a family firm’s emphasis on socioemotional wealth and its ability to achieve organisational ambidexterity. Although there are studies that suggest the presence of higher levels of ambidexterity in family firms, no studies have previously applied the socioemotional wealth framework in the context of organisational ambidexterity. Thereto, no previous studies have provided an explanation as to why there seems to exist a positive relationship between family ownership and organisational ambidexterity. The empirical data of the study consists of interviews with two case companies that are wholly owned and operated by the owner family. The interview data has been processed using thematic analysis. The results are structured around three main themes, decision-making process, motives guiding strategy, and corporate culture, as well as seven subthemes, that were found prominent in the interview material. The themes have served as the basis for five propositions that centre on the connection between socioemotional wealth and its impact on organisational ambidexterity. Finally, we conclude that socioemotional wealth has both positive and negative impact on organisational ambidexterity in the context of the two case companies. The study contributes to the fields of organisational ambidexterity and family business through the establishment of potential connections between the two concepts, and thus sheds light on an observed, yet unexplored, topic.
StudyofRadialVibration Impact onFrictionandTorqueofRotary Drill String

During extended-reach well drilling, the torque of a rotary drill string is too large in the horizontal section, which results in the failure of the drill string. +e effect of radial vibration on the friction and torque of the rotary drill string is unclear. In this work, first, the principle of the impact of radial vibration on the friction and torque of the rotary drill string in the horizontal section is analysed. +en, joints with an elliptical outer edge of the section are designed, which can generate low-amplitude vibration as the drill string rotates owing to the interaction with the wellbore wall. +e radial vibration characteristics can be tuned by changing the major to minor radius ratio of the ellipse. A self-developed experimental device was designed to test the performance of tools with reduced friction and torque. +e drill string torque with different penetration rates, rotation speeds, and ratios of the major radius to minor radius of the ellipse were systematically studied. +e experimental results show that the average and the maximum amplitudes of the torque fluctuation first decrease to the lowest value and then increase with the increase of the ratio. When the ratio reaches 1.065, the average and the maximum amplitudes of the torque fluctuation evidently reduce; therefore, a joint with a ratio of 1.065 can effectively reduce frictional torque. +e average torque reduces when the penetration rate and rotation speed decrease. At rotation speeds of 45 and 60 r/min, the maximum amplitude of torque fluctuation increases first and then decreases with an increase in penetration rate, and it reaches a maximum value at a penetration rate of 22.5m/h. +e fundamental frequency of torque fluctuation is almost linearly related to rotation speed, which is irrelevant to the penetration rate and the ratio of major to minor radius of the ellipse.
Using Agile Practice for Student Software Projects

Agile methodology as a relatively new approach to software engineering is becoming more popular in both industry and academia. Learning agile software development methodologies will unquestionably increase the capabilities and competences of our students as entry-level software engineers. However, how agile methods and techniques should be taught at the undergraduate level in additional to traditional approaches is still being debated. This study was conducted on a studentprogramming project, with sample size of 23 students from the Informatics Engineering course. The Scrum methodology was adopted and 28 user stories and 4 sprints were created. The results indicate a significant impact on students’ skill improvement and let them to have the first contact with real projects and clients. Besides that, the students agree that the adoption of the Scrum methodology helped them to improve the participation and collaboration. However, some issues were also detected in terms of communication and tasks planning. Therefore, we proposed some polities that could help and boost the software development process inside a classroom.
models defined in Complex Systems A geometric model for the generation of

When studying and modelling Complex Systems where there can be a considerable number of variables and relations, it is very important to obtain methodologies that help us to model natural phenomena, these being phenomena present in the physical world and real life. Hypothetically, if we consider a relation defined by a set of variables, ( ) 1 2 , ,. , n y f x x x = , symbolic and numerical methodologies can be obtained. This article presents a model of n-dimensional finite elements that provides the basis for defining a numerical methodology for studying and modelling complex systems. The use of n-dimensional elements then allows us to represent the relation using the values of the same for a finite number of points, this being carried out by resolving an optimization problem. To obtain the geometric model it was necessary to use the correct data structure design and programming to allow effective management of the acquisition and storage of the elements, the nodes considered for each, as well as the functions and procedures needed to approach the problem of optimisation. Finally, we applied the methodology to determine the geometric model and the problem of optimization to study and model an environmental problem
Three-dimensional transient numerical simulation of engine intake flow

To meet more and more stringent emission requirements and improve the economical performance, organizing reasonable gas motion in vehicle engine's cylinder is very important. However, gas motion in the cylinder is mainly affected by the intake flow process. In this paper, three-dimensional transient numerical simulation is studied for the intake flow process in the vehicle engine by using the arbitrary Lagrangian-Eulerian method and a new proposed dynamic grid generation method. Turbulence effect is represented by a revised k-e model. The calculated results reveal the three-dimensional transient flow characteristics of engine intake process, which give important information for the optimal design of engine intake system.
Redacted for privacy

The identity and distribution of ant species preying on the western spruce budworm (Choristoneura occidentalis Freeman) was investigated in eastern Oregon and western Montana. A sticky trap was developed to index ant foraging activity in the canopy by intercepting ants falling from the tree as they traveled between canopy and ground. For all common ant species, trap catches were highly correlated with the average number of ants moving up the tree bole.
Mean-ﬁeld cosmic dynamo and curvature vs turbulence spectrum in Riemannian space

that the curvature energy spectrum of the turbulent dynamo is similar to the Kolmogorov spectrum. Recently Mizeva et al [Doklady Physics (2009)] have shown the the slope of the turbulent spectrum may grow from − 1 . 88 to 2 , as shown here from curvature spectrum in turbulent dynamos. Similar enhancements of turbulence in Friedmann cosmology have been obtained by Brandenburg et al [Phys Rev D (1997)].
Heterogeneous arrival streams, burstiness and packet discarding : a study of individual packet loss

Author(s): Bae, Jaime Jungok; Suda, Tatsuya; Simha, Rahul | Abstract: This paper considers a queueing system with a finite buffer and multiple heterogeneous arrival streams. We focus on Markov Modulated Arrival Processes with differing burstiness and investigate the loss of individual arrival streams when the parameters of the heterogeneous arrival streams are varied.Our analysis follows a new stochastic integral approach and extends existing results for continuous-time Markov Modulated Poisson Arrival Processes to include both continuous-time and discrete-time treatments of multiplexed heterogeneous Markov Modulated Arrivals. In addition, we derive loss probabilities for a priority packet discarding scheme (a congestion control mechanism suitable for high-speed networks). Several interesting numerical results are presented; we introduce a new characterization of an arrival stream, which we refer to as self-loss, and use this to qualitatively predict the effects of multiplexing bursty streams with non-bursty streams.
Top-down, bottom-up or middle-out? Avoiding extraneous detail and over-generality in marine ecosystem models

: The paper by Hannah et al. (this volume) invokes foodweb theory and the ideas of complexity theory to guide the construction of models of intermediate complexity, which sacrifice explicit process detail to increase the number of interacting components of the system and simulate the web of feedback loops. This approach has its merits, if best practice modelling guidelines are followed and the method is used well. However, if this is not the case then the fundamental weakness of the intermediate model approach is that it may end up producing models that are over general and therefore not useful. To make the most
Fire Detection and Localization Method Based on Deep Learning in Video Surveillance

Fire detection and localization in video surveillance had become a particularly important part of disaster rescue. Considering the fire detection and localization of slow detection speed, low detection accuracy, and low localization precision in video surveillance, we proposed a fire detection and localization method based on deep learning. The first thing we improved the SuperPoint method to extract video keyframe in video surveillance. The next thing we employed Convolutional Neural Network (CNN) model to detect the fire on the extracted video keyframes. The last thing we located the fire via superpixel and CNN on the extracted video keyframes which broke out a fire. The experimental results on open fire dataset revealed that the recall of keyframe extraction reached 0.83, the precision of fire detection reached 0.96 and the F1-score of fire localization reached 0.90. Our method realized rapid and accurate detection and precise localization of fire in video surveillance.
Further calibration and validation of FLORIS with wind tunnel data

This paper compares the accuracy of four different FLORIS model implementations characterized by increasing levels of accounted physics. The predictions of each model were tested against experimental observations obtained from wind tunnel tests of a cluster of three scaled wind turbines. The experiments were conducted for a wide range of environmental conditions, and mainly with yawed turbines. The results showed a significant improvement in the accuracy of the base model by adding more details to the physical effects of the simulation, such as secondary steering and a heterogeneous flow field. It is also interesting to note that the FLORIS predictions become particularly accurate when considering inflow-dependent power losses in yaw-misaligned conditions.
WakeNet 0.1 - A Simple Three-dimensional Wake Model Based on Convolutional Neural Networks

Deep convolutional neural networks are a promising machine learning approach for computationally efficient predictions of flow fields. In this work we present a simple modelling framework for the prediction of the time-averaged three-dimensional flow field of wind turbine wakes. The proposed model requires the mean inflow upstream of the turbine, aerodynamic data of the turbine and the tip-speed ratio as input data. The output comprises all three mean velocity components as well as the turbulence intensity. The model is trained with the flow statistics of 900 actuator line large-eddy simulations of a single turbine in various inflow and operating conditions. The model is found to accurately predict the characteristic features of the wake flow. The overall accuracy and efficiency of the model render it as a promising approach for future wind turbine wake predictions.
A six degree-of-freedom set-up for wind tunnel testing of floating wind turbines

In this paper we present a six-degree-of-freedom (DoF) experimental set-up for wind tunnel testing of floating offshore wind turbines (FOWTs). The system is composed of a 6-DoF Stewart platform that can be used to mimic realistically the motions of a floating turbine at laboratory scale. The platform is specifically made for the Model Wind Turbine Oldenburg 0.6 (MoWiTO 0.6). First, the methodology followed to design the system as well as the scaling issues are depicted. Then, the characterisation of the platform is presented. Finally, limitations of the set-up are discussed.
Sensitivity analysis and Bayesian calibration of a dynamic wind farm control model: FLORIDyn

FLORIDyn is a parametric control-oriented dynamic model suitable to predict the dynamic wake interactions between wind turbines in a wind farm. In order to improve the accuracy of FLORIDyn, this study proposes to calibrate the tuning parameters present in the model by employing a probabilistic setting using the UQ4WIND framework. The strategy relies on constructing a surrogate model (based on polynomial chaos expansion), which is then used to perform both global sensitivity analysis and Bayesian calibration. For our analysis, a nine wind turbine configuration in a yawed setting constitutes the test case. The results of sensitivity analysis offer valuable insight into the time-dependent influence of the model parameters onto the model output. The model parameter tied to the turbine efficiency appear to be the most sensitive parameter affecting the model output. The calibrated FLORIDyn model using the Bayesian approach yield predictions much closer to the measurement data, which is equipped with an uncertainty estimate.
Tight Source Domain Match for Partial Domain Adaptation Based on Maximum Density

Unsupervised domain adaptation (UDA) aims at transferring knowledge between a well-labelled ’source domain’ and an unlabelled ’target domain’ by decreasing distribution discrepancy. In real scenario, partial domain adaptation (PDA), where target domain only includes part of the classes of source domain, is adopted as fully-shared label space is often unavailable. Non-identical label spaces across domains lead to performance degradation due to source-unique classes being mis-matched to the target domain, i.e. negative transfer of the target domain. Although existing PDA approaches have produced promising results, they still confront with negative transfer problem without rigorous generalization bounds. In our work, a novel PDA model has been proposed based on margin disparity and maximum source intra-class density divergence (MDSD). It matches the feature distributions with shared labels and congregates source samples in the source with affirmative labels. Removing maximum target density with pseudo labels, it effectively avoids over-fitting and accelerates learning speed. In addition, we construct a new garbage classification dataset, which is comprised of source domain - Product (Pr) and target domain - Garbage (Ga) for PDA validation. Experiments show that our proposed unsupervised partial domain adaptation method has a good performance on Office-31, Office-Home and Pr-Ga datasets.
Sketch Based Image Retrieval for Architecture Images with Siamese Swin Transformer

Sketch-based image retrieval (SBIR) is an image retrieval task that takes a sketch as input and outputs colour images matching the sketch. Most recent SBIR methods utilise deep learning methods with complicated network designs, which are resource-intensive for practical use. This paper proposes a novel compact framework that takes the siamese network with image view angle information, targeting the SBIR task for architecture images. In particular, the proposed siamese network engages a compact SwinTiny transformer as the backbone encoder. View angle information of the architecture image is fed to the model to further improve search accuracy. To cope with the insufficient sketches issue, simulated building sketches are used in training, which are generated by a pre-trained edge extractor. Experiments show that our model achieves 0.859 top-one accuracy exceeding many baseline models for an architecture retrieval task.