Miracle-dz/UniFAR-FTUs huggingface dataset:
Amplifying effects of recurrent drought on the dynamics of tree growth and water use in a subalpine forest.

Despite recent advances in our understanding of drought impacts on tree functioning, we lack knowledge about the dynamic responses of mature trees to recurrent drought stress. At a subalpine forest site, we assessed the effects of three years of recurrent experimental summer drought on tree growth and water relations of Larix decidua and Picea abies, two common European conifers representative for contrasting water-use strategies. We combined dendrometer and xylem sap flow measurements with analyses of xylem anatomy and non-structural carbohydrates and their carbon-isotope composition. Recurrent drought increased the effects of soil moisture limitation on growth and xylogenesis, and to a lesser extent on xylem sap flow. P. abies showed stronger growth responses to recurrent drought, reduced starch concentrations in branches and increased water-use efficiency when compared to L. decidua. Despite comparatively larger maximum tree water deficits than in P. abies, xylem formation of L. decidua was less affected by drought, suggesting a stronger capacity of rehydration or lower cambial turgor thresholds for growth. Our study shows that recurrent drought progressively increases impacts on mature trees of both species, which suggests that in a future climate increasing drought frequency could impose strong legacies on carbon and water dynamics of treeline species. This article is protected by copyright. All rights reserved.
Proposal of Semantic Annotation for German Metadata Using Bidirectional Recurrent Neural Networks

The distributed nature of our digital healthcare and the rapid emergence of new data sources prevents a compelling overview and the joint use of new data. Data integration, e.g., with metadata and semantic annotations, is expected to overcome this challenge. In this paper, we present an approach to predict UMLS codes to given German metadata using recurrent neural networks. The augmentation of the training dataset using the Medical Subject Headings (MeSH), particularly the German translations, also improved the model accuracy. The model demonstrates robust performance with 75% accuracy and aims to show that increasingly sophisticated machine learning tools can already play a significant role in data integration.
Wavelet Neural Network Methodology for Ground Resistance Estimation

The present study aims to develop an estimation model for the ground resistance fluctuation. The need of engineers to have in their disposal a flexible and reliable tool, for estimating and predicting grounding systems behavior, is what actually motivated this workscope. It is well-known that grounding systems are a key of high importance for the safe operation of electrical facilities, substations, transmission lines and, generally, electric power systems. Yet, in most cases, electrical engineers and researchers have few data about the soil resistivity variation at the terrain of interest in design phase and, even more, the periodic measurement of ground resistance is hindered very often by the residence and building infrastructure, after the installation. Thus, the proposed model aspires to offer a reliable solution to estimation problems of
A NOVEL PCM THERMO SIPHON DEFROST SYSTEM FOR A FROZEN RETAIL DISPLAY CABINET

An energy efficient method of defrosting the evaporator on a frozen retail display cabinet was developed and its performance compared with that of the existing electric defrost. The cabinet was modified so that either defrost system could be deployed, leaving the rest of the system operation untouched. Performance of the cabinet during EN23953 standard tests was compared. Total energy consumption during the tests was 40% lower with the novel defrost. This was partly due to elimination of the use of electrical defrost power (which reduced direct electrical power by 39%). Since the system leads to lower liquid refrigerant temperatures at the expansion valve there is a saving in compressor power for the same refrigeration effect and as the defrost is quicker, the temperature excursions inside the cabinet are smaller, reducing the amount of heat which has to be removed after a defrost. The cabinet can also be run at a higher evaporating temperature, further reducing energy consumption.
Monitoring Data Transmission Technology in 5T System Based on Message

The problems of transmission conflict of monitoring data and data block-up in 5T system were analyzed,in which train infrared hotbox detection system,truck performance detection system,trackside acoustic diagnosis system for fault in early stage of wagon rolling bearing,trouble of moving freight car dynamic image detection system,train coach running diagnosis system were included.An information model of 5T system was constructed based on the safety degree analysis of train running reflected by the monitoring data in order to solve these problems.A dynamic priority queue transmission flow was designed based on message queue technology.A model of monitoring data transmission priority based on data type,warning grade,vehicle type and speed in 5T system was constructed on the basis of quantizing the priority influencing factors.The resolution for priority factor was converted to multi-objective decision-making model solution with partial weight information.A single-objective optimal model was constructed and solved to get the undetermined weight vector.Finally the transmission queue was adjusted based on the solution of the priority factor and the adjustment steps for priority queue.A prototype system of monitoring data transmission was developed based on these principles.Feasibility and effectiveness of the technology scheme were verified by the experimental results.
N6-substituted cAMP Analogs Inhibit bTREK-1 K + Channels and Stimulate Cortisol Secretion by a PKA-Independent Mechanism

Bovine adrenal zona fasciculata (AZF) cells express bTREK-1 K + channels whose inhibition by cAMP is coupled to membrane depolarization and cortisol secretion through complex signaling mechanisms. cAMP analogs with substitutions in the 6 position of the adenine ring selectively activate cAMP-dependent protein kinase (PKA), but not exchange proteins activated by cAMP (Epacs). In whole cell patch clamp recordings from AZF cells, we found that 6-benzoyl-cAMP (6-Bnz-cAMP) and 6-monobutyryl-cAMP (6-MB-cAMP) potently inhibit bTREK-1 K + channels, even under conditions where PKA activity was abolished. Specifically, when applied through the patch electrode, 6-Bnz-cAMP inhibited bTREK-1 with an IC 50 of less than 0.2 µM. Inhibition of bTREK-1 by 6-Bnz-cAMP was not diminished by PKA antagonists including H-89, Rp-cAMPS, PKI(6-22) amide, and myristoylated PKI(14-22) applied alone or in combination, externally and intracellularly through the patch pipette. Under similar conditions, these same antagonists completely blocked PKA activation by 6-Bnz-cAMP. Inhibition of bTREK-1 by 6-Bnz-cAMP was voltage-independent and eliminated in the absence of ATP in the pipette solution. 6-Bnz-cAMP also produced delayed increases in cortisol synthesis and the expression of CYP11a1 mRNA that were only partially blocked by PKA antagonists. These results indicate that 6-Bnz-cAMP and other 6-substituted cAMP analogs can inhibit bTREK-1 K + channels and stimulate delayed increases in cortisol synthesis by AZF cells through a PKA- and Epac-independent mechanism. They also suggest that ACTH and cAMP function in these cells through a third cAMP-dependent protein. Finally, although 6-modified cAMP analogs exhibit high selectivity in activating PKA over Epac, they also may interact with other unidentified proteins expressed by eukaryotic cells.
DEVELOPMENT AND EVALUATION OF A METHOD TO QUANTIFY RUGBY PLACE KICK PERFORMANCE FROM INITIAL BALL FLIGHT DATA

The purpose of this study was to develop and evaluate a method for quantifying rugby place kick performance using a metric that represents field-based performance but relies only on data typically available within a laboratory setting. A mathematical model was developed to predict the flight path of a rugby ball using equations of projectile motion and initial ball flight kinematics as inputs. The accuracy of the model predictions were then evaluated against empirical data collected from eight place kicks taken 22 m from the goalposts on a rugby pitch. The model estimated the position of the ball at the instant it reached the goalposts with a root mean square error of 0.65 m (2.9% of the range). It is intended that this method will provide an applied outcome measure that is relevant to players and coaches.
Study of long-term sustained operation of gaseous detectors for the high rate environment in CMS

The muon system of CMS aims to provide an efficient and fast identification of the muons produced in the proton-proton collisions. However, the forward region of the end-caps is only instrumented with Cathode Strip Chambers. This lack of redundancy will be problematic after the high-luminosity upgrade of the LHC (HL-LHC), for which the increase of the background rate would degrade the Level-1 trigger performance and thus the selection of interesting physics channels. The goal of the CMS muon upgrade is to maintain the L1 trigger rate with maximum selection efficiency in order to fully exploit the HL-LHC. The CMS GEM Collaboration has proposed to instrument the vacant highetaregion of the muon end-caps with Gas Electron Multiplier (GEM) detectors, called GE1/1chambers.The Ph.D. subject proposed by the CMS GEM Collaboration aims to demonstrate that the GE1/1technology is the most suitable choice for the upgrade of the muon end-caps. Three main researchprojects were conducted in this context. The first project included the precise measurement of the fundamental characteristics and the detection performance of the triple-GEM detectors produced with the single-mask technique. Those characteristics are essential to ensure that the detectors can operate in the forward region of CMS. The second project was focused on the long-term operation of GE1/1 detectors, in particular the study of the aging phenomenon, which includes all the processes that lead to a significant and permanent degradation of the performance of the detectors. Several aging tests were performed at the CERN irradiation facilities to prove that the GE1/1 chambers can operate during at least 10 yearsat HL-LHC without suffering from performance losses. The excellent properties measured during the R&D phase led to the approval of the GE1/1 project by the CMS Collaboration. The third project, conducted in the framework of the mass production,consisted of developing of the main steps of the Quality Control of the GE1/1 chambers.
Arrested decisions: the effects of information latency on high-risk decision-making

This research will evaluate how changes in information latency during computer deployments affect performance of high risk decision makers. High risk decisions and decision-makers, in this case, are police officers deciding whether or not to arrest an individual based on information provided via computer from a distant source. There are three critical research pillars for this research. First, the impact on performance of naturalistic decision-making (NDM) research described for high-risk decision making through the use of a recognition-primed decision (RPD) model (Klein 1998) will be observed. Next, media richness posits richer media has more impact on equivocal tasks. Media of different “richness” was tested for impacts on decision performance. The recognition primed decision model, portions of media richness, and information thresholds are integrated to provide a model to relate information latency effects on high-risk decision-making. This model was evaluated using three wireless computer deployments by a city-county police department. Using archival data, subjects in this research, 406 mobile police officers, were followed over a six year period to evaluate the impact of varying media richness (from radio verbal access to textural computer queries of varying types) using computers of varying access-information retrieval rates. Outcome measures of arrest warrants served and physical arrests based on probable cause (where a reasonable officer would believe that a person had committed a criminal violation of local, state or federal law), were recorded over all interventions. User performance traits are shown to be a major influencing factor in outcomes and processes changes. Finally, this research shows how individual user performance traits impact high-risk decision performance more than latency but only with high performers in the organization. Information latency is shown to have little impact on low performers. User performance traits may explain the productivity paradox1 with computers. 1Brynjolfsson, E. and L. Hitt (1998). “Beyond the Productivity Paradox: Computers are the Catalyst for Bigger Changes. ” Communications of the ACM 41(8): 49–55.
S TAGED INDEPENDENT LEARNING : T OWARDS DECEN - TRALIZED COOPERATIVE MULTI - AGENT R EINFORCE - MENT L EARNING

We empirically show that classic ideas from two-time scale stochastic approximation (Borkar, 1997) can be combined with sequential iterative best response (SIBR) to solve complex cooperative multi-agent reinforcement learning (MARL) problems. We first start with giving a multi-agent estimation problem as a motivating example where SIBR converges while parallel iterative best response (PIBR) does not. Then we present a general implementation of staged multi-agent RL algorithms based on SIBR and multi-time scale stochastic approximation, and show that our new methods which we call Staged Independent Proximal Policy Optimization (SIPPO) and Staged Independent Q-learning (SIQL) outperform state-of-the-art independent learning on almost all the tasks in the epymarl (Papoudakis et al., 2020) benchmark. This can be seen as a first step towards more decentralized MARL methods based on SIBR and multi-time scale learning.
Reduced-order modeling of 4D flow MRI and CFD in stenotic flow using Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD)

Severe arterial stenosis encompasses complex flow structures especially when the blood flow rate exceeds the critical Reynolds number (Re ≥ 2000), resulting in ow instability and turbulence. Uncovering reduced-order ow characteristics in blood flow data facilitate understanding flow physics and efficient data-driven modeling. In this paper, we used Computational Fluid Dynamics (CFD) and 4D flow MRI data in a phantom model of arterial stenosis with 87% degree of narrowing for performing Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) on the velocity and pressure data. We found the required modes to reconstruct the CFD and 4D flow MRI velocity and pressure data in the phantom model and identified the most energetic modes with temporal dynamics of coherent structures. In addition, we evaluated the compromise between the simplicity and accuracy of the reconstructed data. These data-driven modeling techniques have the potential to reduce the complexity of 4D flow MRI data. We envisage that it can ultimately be applied to enhancing the resolution, denoising 4D flow MRI data, and impacting data collection requirements.
Comparative Mitochondrial Genome Analysis of Mamestra configurata (Lepidoptera: Noctuoidea: Noctuidae) and Other Noctuid Insects Reveals Conserved Genome Organization and Phylogeny

Abstract Mitochondrial genomes (mitogenomes) advance our understanding of molecular evolution and phylogenetic relationships. In this study, the mitogenome of Mamestra configurata was assembled, annotated, and analyzed. The total length of its genome was 15,322 bp; the A+T content accounted for 81.2%. Both the AT and GC skew values (–0.003 and –0.182) in the mitogenome of M. configurata were negative. Compared with their ancestral insects (trnI-trnQ-trnM), the gene sequence showed a typical trnm rearrangement (trnM-trnI-trnQ). Except for cox1, all the protein-coding genes were initiated with ATN. All tRNAs except trnS1 were of the four-leaf grass type. According to phylogenetic analysis, we found that M. configurata and Protegira songi clustered together in one clade with high node support values. Based on Bayesian inference and maximum likelihood methods, the phylogenetic results revealed that M. configurata was closely related to Protegira songi, the Erebidae was sister to (Nolidae + [Euteliidae + Noctuidae]), Doidae and Notodontidae is sister to the other families of Noctuoidea, respectively. Our results may provide a useful reference for the intensive study of the phylogeny of Noctuidae.
Study on the technical parameters model of the functional components of cone crushers

Abstract A cone crusher is a machine that crushes rock materials with high efficiency and low power consumption; it is one of the typical road construction equipment. To improve the production efficiency, mechanical performance, and crushing performance of the cone crusher, thus increasing profit, this study used Discrete element method (DEM) particle analysis software to optimize the structure of the moving cone, studied the crushing effect of the crusher, and carried out kinetics analyses. Based on DEM, the structure of the cone crusher cavity was analyzed and optimized. A Y51 cone crusher was selected as a representative example to study its moving cone structure. By analyzing the factors that affect the performance and efficiency of the crusher, the precession angle, base angle, shape, and rotational speed of the moving cone were optimized. Using the Genetic Algorithm-Support Vector machine method (GA-SVW), the optimal combination of parameters was determined, and the key parts of the crusher were thus optimized.
Shear capacity prediction of steel plate shear walls with precompression from columns

This paper investigates the shear capacity of the unstiffened steel plate shear walls with gravity loads from the adjacent boundary columns that is produced during the construction process. The distribution and transferring of gravity loads between boundary columns and the infill steel plate are proposed. Then, the infill steel plate is partitioned into 3 zones bounded on the effective length, the inclination angle, and shear capacity of each zone that is proposed and discussed, and the shear capacity of the infill steel plate is summed over the 3 zones. Finally, based on the three specimens tested by Park et al. (2007), shear capacity prediction of 18 more numerical steel plate shear wall specimens with the axial stresses of the boundary columns equal to 50 MPa, 100 MPa, 150 MPa, 200 MPa, 250 MPa, and 300 MPa are analyzed.
Nonfragile H ∞ tracking control strategies for classes of linear and bilinear uncertain Takagi-Sugeno fuzzy systems

This paper presents fuzzy tracking control strategies for classes of linear and bilinear Takagi-Sugeno Fuzzy System with Uncertainties and Disturbances (T-S FSUD). For both classes, the Lyapunov direct approach and the parallel distributed compensation concept are used to design nonfragile H∞ tracking controllers, which ensure the robust asymptotic stability of augmented systems despite the presence of parameter uncertainties, external disturbances, and controllers fragility. Besides that, based on the Schur complement, the separation lemma, and through some variable transformations, sufficient stability conditions of each augmented T-S FSUD are established and formulated in terms of linear matrix inequalities. Finally, numerical simulations are carried out to demonstrate the validity and the applicability of designed control schemes on tracking control of an inverted pendulum and a nonlinear mechanical system.
Impact of nanoparticle shape on magnetohydrodynamic stagnation-point flow of Carreau nanoliquid: A comparative study

In this paper, a numerical computational work is carried out to investigate the significance of nanoparticle shape on magnetohydrodynamic stagnation-point flow of Carreau nanoliquid caused by a horizontally moving thin needle. The drive and thermal transport nature of Ti6Al4V+Ethylene glycol nanoliquid under the stimulus of space-dependent heat source and magnetized force is discussed numerically. The novelty of this work is to obtain the simultaneous solutions for three different shapes of nanoparticles namely spherical, cylindrical and laminar. The flow governing partial differential equations are transformed into ordinary differential equations with appropriate similarity variables and solved numerically by using Runge–Kutta and Newton's approach. Numerical outcomes of velocity and thermal distributions under the influence of different physical parameters are illustrated via graphical trends, wall friction and rate of heat transfer are interpreted using tabular values. It reveals from results that the thermal transfer performance of the Carreau nanoliquid is advanced when spherical shaped nanoparticles are used as compared with cylindrical and laminar-shaped nanoparticles. Also, it is witnessed that needle thickness parameter plays vital role in augmenting thermal transport rate of the nanoliquid.
Study of optimum welding performance in friction stir welding of dissimilar Mg alloys using integrated RSM-TLBO algorithm

Lightweight with excellent strength of magnesium alloys has attracted its use in transportation industries but difficulty in fusion welding of magnesium alloys restricts its application. The present research investigates solid state friction stir welding of dissimilar AZ31-AZ91 magnesium alloys with aim to achieve optimum quality welds. Surface roughness, microstructure and mechanical properties of these joints have been investigated at different tool rotational speed, welding speed and tool shoulder diameter. Maximum joint strength obtained is 89.71% (as compare to AZ31) which is more than the previously reported joint strengths of dissimilar magnesium alloys. Further, mathematical relations for responses have been developed and utilised for multi-objective optimization using teaching-learning-based optimization algorithm. Eventually, teaching-learning-based optimization algorithm results suggest that the optimum value of surface roughness (3.3925 µm), grain size (12.6869 µm), tensile strength (237.9621 MPa), microhardness (69.3652 Hv) and flexural strength (333.2285 MPa) can be achieved at 921 rpm rotational speed, 30 mm/min welding speed and 15 mm shoulder diameter with overall improvement in multiple responses.
Electric conductivity and dielectric relaxation properties of BiFeO3-YMnO3 solid solution

Abstract This manuscript presents a systematic study of conductivity and dielectric relaxations in the solid solution of (BiFeO3)1-x -(YMnO3)x for compositional range (0.0 ≤ x ≤ 0.2) as function of frequency, temperature, and magnetic field. The samples have been synthesized by combustion method. The thermal activations of dc-conductivity and relaxation time obey Arrhenius behavior for, x = 0.0, 0.025, 0.05 but follow variable range hopping of small polarons above, x ≥ 0.075 with activation energy 0.45 eV. The compositional time-temperature superposition of dielectric modulus data suggests that conduction mechanism changes with composition. The bulk capacitance decreases with increase in magnetic field.
EMOTE: An interactive online tool for designing real-time emotional AR visualizations

In a future when augmented vision becomes a part of our daily lives, some might want or need to highlight their emotions by visuals on or around their bodies like wearing a prosthesis or an expressive make-up. This might especially be useful for situations where one cannot express their own emotions or read others’. To help the design process of affective augmentations, we developed EMOTE; an online interactive tool that presents a framework to guide designers while designing emotion visualizations for AR. We conducted an online workshop with 24 participants to evaluate the framework and the online tool. In this paper, we share insights on user experience with this tool, the effect of framework on the design process and how the framework can be expanded.