Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of different management strategies against Ectomyeloïs ceratoniae Zeller (Lepidoptera: Pyralidae) in citrus orchards in Tunisia

ABSTRACT Ectomyelois ceratoniae (Zeller) is a cosmopolitan pest that affects many crops worldwide. The present study was performed to refine our knowledge about density and damage of this pest on Navel oranges in northern Tunisia and to evaluate the effectiveness of four alternative methods including, cultural control, mass trapping, Trichogramma cacoeciae (Marchal) releases and mating disruption. Results showed that E. ceratoniae populations increased from April to November. All trials were effective in decreasing E. ceratoniae populations on citrus fruits. The most effective management was mating disruption combined with T. cacoeciae release (30,000 Trichogramms/ha), with a reduction rate of E. ceratoniae of 62.8% after treatment. Mass trapping using delta traps combined with Trichogramma releases (25,000 T/ha) may be a promising alternative for limiting E. ceratoniae populations. It has also been shown that a density of 10 delta traps/ha can reduce the infestation rate of E. ceratoniae. Furthermore, control by successive T. cacoeciae releases at a density of 20,000 T/ha shows its effectiveness. Our results for improving management of E. ceratoniae in citrus orchards are highlighted and discussed herein.
Modular Dynamic Model of Multi-Shaft Gas Turbine and Validation Test

The paper deals with the development of a component module library necessary to study multi-shaft gas turbine power plants. In particular the paper presents: - the features of the software environment used to develop the gas turbine modular dynamic model; - for each gas turbine component, the whole form of the dynamic physical equations and their simplified final expression suitable for the software environment requirements; - the procedure relative to the building of the gas turbine modules. In order to validate the created gas turbine modules, the transient behavior of a twin-shaft industrial gas turbine, simulated by connecting the new modules, was compared with experimental data available in literature. The values obtained by the simulation turn out to be in agreement with the experimental data.
Room acoustic modelling of textile materials hung freely in space: from the reverberation chamber to ancient churches

The aim of this study is to investigate how sound absorbing materials like curtains should be modelled in geometrical acoustic (GA) software when hung freely in space. The use of these tools is widespread today. Whatever the scope of the simulation, dealing with textile materials can be particularly challenging as they both absorb and transmit sound, and absorption is dependent on distance of the walls. Therefore, care must be taken to enter properly validated data. Absorption coefficients found in the literature are measured with samples close to wall, and are not suitable when materials are hung freely. The effects of material placement on both absorption and transmission coefficients were therefore investigated using scaled-down physical models of a reverberant chamber and a church. Subsequently, GA models of both spaces were used to demonstrate that simulated results are reliable assuming that absorption and transmission coefficients are correctly determined.
Breakdown of Light Vehicle Crashes by Pre-Crash Scenarios as a Basis for Countermeasure Development

This paper presents a statistical description of light vehicle (passenger vehicles, sports utility vehicles, vans, and pickup trucks) crashes in terms of their major crash types, physical setting, and concomitant pre-crash scenarios based on the 2000 General Estimates System national crash database. This database contains variables that categorize the pre-crash situation and identify the vehicle movements and critical events immediately prior to the collision. This crash analysis supports the U.S. Department of Transportation's Intelligent Vehicle Initiative to solve traffic safety problems through the development and deployment of vehicle-based crash avoidance systems using advanced technologies. In the year 2000, light vehicles were involved in about 6,133,000 or 96.0% of all police-reported crashes on U.S. roadways. A breakdown of these crashes revealed 10 different crash types. Rear-end, crossing paths, off-roadway, and lane change crash types comprised the majority of these crashes with a combined frequency of 5,240,000 crashes. About 39.6% of all light vehicle crashes occurred at non-junctions, while 24.5% and 20.4% of all light vehicle crashes happened respectively at intersections and near intersections. Further breakdown of the four most dominant crash types identified 25 dynamically distinct pre-crash scenarios that influence the design of the sensory and decision-making elements for potential countermeasure systems.
Machine Learning Based Restaurant Sales Forecasting

To encourage proper employee scheduling for managing crew load, restaurants need accurate sales forecasting. This paper proposes a case study on many machine learning (ML) models using real-world sales data from a mid-sized restaurant. Trendy recurrent neural network (RNN) models are included for direct comparison to many methods. To test the effects of trend and seasonality, we generate three different datasets to train our models with and to compare our results. To aid in forecasting, we engineer many features and demonstrate good methods to select an optimal sub-set of highly correlated features. We compare the models based on their performance for forecasting time steps of one-day and one-week over a curated test dataset. The best results seen in one-day forecasting come from linear models with a sMAPE of only 19.6%. Two RNN models, LSTM and TFT, and ensemble models also performed well with errors less than 20%. When forecasting one-week, non-RNN models performed poorly, giving results worse than 20% error. RNN models extended better with good sMAPE scores giving 19.5% in the best result. The RNN models performed worse overall on datasets with trend and seasonality removed, however many simpler ML models performed well when linearly separating each training instance.
Almost Sure Consensus of Multi-Agent Systems: An Intermittent Noise

In this brief, the almost sure exponential consensus of multi-agent systems is investigated. A consensus protocol is designed with aperiodically intermittent communication noise rather than common continuous communication noise. Based on the consensus protocol, some sufficient conditions are given. Moreover, theoretical results show that the larger the noise control gain is, the larger the convergence rate of exponential convergency becomes in an almost sure sense. Besides, when the consensus protocol with aperiodically intermittent communication noise degenerates into one with periodically intermittent communication noise or one with common continuous communication noise, two corollaries are presented respectively. Then, the main results are used to consider almost sure exponential consensus of oscillator systems, and some simulations are provided.
Simulation of various nanoelectronic devices based on 2D materials

The development of field-effect transistors (FETs), resonant-tunneling diodes (RTDs), vertical heterostructures and other device structures on the basis of 2D materials is one of the important tasks for producing a new element base for micro and nanoelectronics. The wave function formalism was applied in the development of numerical model of vertical heterostructures based on 2D materials [1, 2]. Combined self-consistent models [3, 4] were adapted for the case of taking into account vertical transport in the conduction band. The influence of various factors on the electric characteristics of the vertical heterostructures based on graphene, h-BN and MoS2 was investigated with the use of the developed model. The IVcharacteristics of such structures were calculated for different number of layers of 2D materials that forms potential barriers and quantum wells. Comparison of the results of simulation of the investigated structures is carried out. A numerical combined model based on a self-consistent numerical solution of the Schrödinger and Poisson equations in the active region of the device was used to calculate the IV-characteristics of GaN/AlGaN-based RTDs with vertical transport [5, 6]. The proposed model was used to study the effect of the aluminum concentration in the barriers on the IV-characteristics of the considered RTDs. Developed quantum drift-diffusion model of FET based on monolayer graphene was described in detail [7, 8]. The model is based on quantum drift-diffusion approximation of carrier transport. Graphene channel is located between topand back-gate dielectrics. With the use of the model simulation of dual-gate FET with channel width 18 μm was considered. A good agreement with experimental data was obtained for number of applied voltages. Adequacy of the model is confirmed by these calculations. The programs realizing the proposed models were included in the nanoelectronic devices simulation system developed at the BSUIR since 1995 [9, 10].
Urinary excretion of heat-shock protein 70 in patients with familial mediterranean fever

Eren Yıldız1, Arife Uslu Gökceoğlu2, Nermin Dindar Badem3, Bülent Alioğlu4 1Department of Pediatrics, University of Health Sciences, Ankara Training and Research Hospital, Ankara 2Department of Pediatric Nephrology, University of Health Sciences, Ankara Training and Research Hospital, Ankara 3Department of Medical Chemistry, Kırıkkale University Faculty of Medicine, Kırıkkale 4Department of Pediatric Hematology, University of Health Sciences, Ankara Training and Research Hospital, Ankara, Turkey Heat-shock protein 70 in patients with familial mediterranean fever Urinary excretion of heat-shock protein 70 in patients with familial mediterranean fever
Vehicle State Estimation by Unscented Particle Filterin Distributed Electric Vehicle

Focusing on the existing problems in vehicle state estimation, such as deficient integrality system and low accuracy, unscented particle filter(UPF) is proposed, which utilizes the characteristic that distribute electric vehicle(DEV) has multi-information sources. Based on the nonlinear vehicle dynamic model, the novel system estimated longitudinal velocity, sideslip angle, yaw rate and tire lateral force simultaneously. In order to improve accuracy of tire lateral force, nonlinear dynamic tire model is utilized. UPF is developed according to the proposed vehicle and tire model. To improve the accuracy of UPF, measurement noise covariance is also self-adaptive regulated. Simulations and experiments show that the proposed method can improve robustness and accuracy of vehicle state estimation.
Polyamine Oxidase Triggers H2O2-Mediated Spermidine Improved Oxidative Stress Tolerance of Tomato Seedlings Subjected to Saline-Alkaline Stress

Saline-alkaline stress is one of several major abiotic stresses in crop production. Exogenous spermidine (Spd) can effectively increase tomato saline-alkaline stress resistance by relieving membrane lipid peroxidation damage. However, the mechanism through which exogenous Spd pre-treatment triggers the tomato antioxidant system to resist saline-alkaline stress remains unclear. Whether H2O2 and polyamine oxidase (PAO) are involved in Spd-induced tomato saline-alkaline stress tolerance needs to be determined. Here, we investigated the role of PAO and H2O2 in exogenous Spd-induced tolerance of tomato to saline-alkaline stress. Results showed that Spd application increased the expression and activities of superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), glutathione reductase (GR), and the ratio of reduced ascorbate (AsA) and glutathione (GSH) contents under saline-alkaline stress condition. Exogenous Spd treatment triggered endogenous H2O2 levels, SlPAO4 gene expression, as well as PAO activity under normal conditions. Inhibiting endogenous PAO activity by 1,8-diaminooctane (1,8-DO, an inhibitor of polyamine oxidase) significantly reduced H2O2 levels in the later stage. Moreover, inhibiting endogenous PAO or silencing the SlPAO4 gene increased the peroxidation damage of tomato leaves under saline-alkaline stress. These findings indicated that exogenous Spd treatment stimulated SlPAO4 gene expression and increased PAO activity, which mediated the elevation of H2O2 level under normal conditions. Consequently, the downstream antioxidant system was activated to eliminate excessive ROS accumulation and relieve membrane lipid peroxidation damage and growth inhibition under saline-alkaline stress. In conclusion, PAO triggered H2O2-mediated Spd-induced increase in the tolerance of tomato to saline-alkaline stress.
Seed extraction using superpixel-based SLIC for interactive image segmentation

Abstract. For complex images, interactive image segmentation can achieve better segmentation performance than other approaches. However, many classical interactive segmentation methods are sensitive to the locations and number of seed pixels. We introduce a seed extraction method to address this issue. First, we propose a robust seed measure to select and mark the seed pixels that cover the whole image. We use the center pixel of each superpixel as a seed. Then, each center pixel is labeled by our seed measure. Second, we propose a relabeling method for addressing isolated seeds. The extracted seeds can be used to locate the initial object area and can serve as the inputs of other interactive segmentation methods to reduce their dependence on user interaction. Extensive experiments on the Berkeley, GrabCut, and MSRA1000 datasets demonstrate the effectiveness of our seed extraction method.
The Intertwining of Technologies and Work Practices

Modern organizations are experiencing an increase in information-related tasks as a consequence of the need for real-time data in competitive environments, improved technological opportunities for information gathering and information usage, and requirements for more legally required registrations. This analysis of agricultural organizations reveals that information in these organizations grows with specialization, and that farmers handle increasing amounts of information related-work practices. These practices are supported by the technologies agricultural organizations adopt. In this research, I examine how Google Glass can function as an embedded element in farmers’ everyday work practices. Through a grounded analysis I show how actors use past experiences, present applications and future possibilities to contextually evaluate demands for digital innovations and work practice. By applying the concept of sociomateriality in my reflective analysis I further discover that Google Glass can facilitate an intertwinement of working practice in specific situations and information related-work. For the innovative intertwinement of situation and information-related work practices to happen the demands for technologies and work practices must be actualized. Additionally, I discuss how this is a new outlook on technology in work practice.
On the use of numerical models for validation of high frequency based damage detection methodologies

This article identifies and addresses current limitations on the use of numerical models for validation and/or calibration of damage detection methodologies that are based on the analysis of the high frequency response of the structure to identify the occurrence of abrupt anomalies. Distributed-plasticity non-linear fiber-based models in combination with experimental data from a full-scale reinforced concrete column test are used to point out current modeling techniques limitations. It was found that the numerical model was capable of reproducing the global and local response of the structure at a wide range of inelastic demands, including the occurrences of rebar ruptures. However, when abrupt sudden damage occurs, like rebar fracture, a high frequency pulse is detected in the accelerations recorded in the structure that the numerical model is incapable of reproducing. Since the occurrence of such pulse is fundamental on the detection of damage, it is proposed to add this effect to the simulated response before it is used for validation purposes.
The effect of 2,4-dichlorophenoxyacetic acid on the production of oat (Avena sativa L.) doubled haploid lines through wide hybridization

Background Development of new cultivars is one of the vital options for adapting agriculture to climate change, and the production of doubled haploid (DH) plants can make a significant contribution to accelerating the breeding process. Oat is one of the cereals with particular health benefits, but it unfortunately still remains recalcitrant to haploidization. Our previous studies have clearly demonstrated that post-pollination with hormone treatment is a key step in haploid production through wide hybridization and indicated it as the most effective method for this species. Therefore, we subsequently addressed the problem of the influence of 2,4-dichlorophenoxyacetic acid (2,4-D) concentration on consecutive stages of DH production. Methods Twenty-nine genotypes were tested, 9,465 florets were pollinated with maize pollen 2 days after emasculation and then treated with 2,4-D at 50 mg/L and 100 mg/L. Results The applied treatments did not reveal any differences in the number of obtained haploid embryos. However, almost twice as many haploid plants formed on MS medium after applying a higher auxin concentration and 20% more successfully acclimatized. Moreover, 100 mg/L 2,4-D treatment resulted in twice as many DH lines that produced almost three times more seeds compared to 50 mg/L treatment. Nevertheless, the results have confirmed the existence of strong genotypic variation, which may significantly limit the development of an effective and economically feasible method that could be incorporated into breeding programs.
Genome-Wide Analysis Indicates a Complete Prostaglandin Pathway from Synthesis to Inactivation in Pacific White Shrimp, Litopenaeus vannamei

Prostaglandins (PGs) play many essential roles in the development, immunity, metabolism, and reproduction of animals. In vertebrates, arachidonic acid (ARA) is generally converted to prostaglandin G2 (PGG2) and H2 (PGH2) by cyclooxygenase (COX); then, various biologically active PGs are produced through different downstream prostaglandin synthases (PGSs), while PGs are inactivated by 15-hydroxyprostaglandin dehydrogenase (PGDH). However, there is very limited knowledge of the PG biochemical pathways in invertebrates, particularly for crustaceans. In this study, nine genes involved in the prostaglandin pathway, including a COX, seven PGSs (PGES, PGES2, PGDS1/2, PGFS, AKR1C3, and TXA2S), and a PGDH were identified based on the Pacific white shrimp (Litopenaeus vannamei) genome, indicating a more complete PG pathway from synthesis to inactivation in crustaceans than in insects and mollusks. The homologous genes are conserved in amino acid sequences and structural domains, similar to those of related species. The expression patterns of these genes were further analyzed in a variety of tissues and developmental processes by RNA sequencing and quantitative real-time PCR. The mRNA expression of PGES was relatively stable in various tissues, while other genes were specifically expressed in distant tissues. During embryo development to post-larvae, COX, PGDS1, GDS2, and AKR1C3 expressions increased significantly, and increasing trends were also observed on PGES, PGDS2, and AKR1C3 at the post-molting stage. During the ovarian maturation, decreasing trends were found on PGES1, PGDS2, and PGDH in the hepatopancreas, but all gene expressions remained relatively stable in ovaries. In conclusion, this study provides basic knowledge for the synthesis and inactivation pathway of PG in crustaceans, which may contribute to the understanding of their regulatory mechanism in ontogenetic development and reproduction.
Joint Patch Weighting and Moment Matching for Unsupervised Domain Adaptation in Micro-Expression Recognition

SUMMARY Unsupervised domain adaptation (DA) is a challenging machine learning problem since the labeled training (source) and unlabeled testing (target) sets belong to di ﬀ erent domains and then have different feature distributions, which has recently attracted wide attention in micro-expression recognition (MER). Although some well-performing un-supervised DA methods have been proposed, these methods cannot well solve the problem of unsupervised DA in MER, a. k. a. , cross-domain MER. To deal with such a challenging problem, in this letter we propose a novel unsupervised DA method called Joint Patch weighting and Moment Matching (JPMM). JPMM bridges the source and target micro-expression feature sets by minimizing their probability distribution divergence with a multi-order moment matching operation. Meanwhile, it takes advantage of the contributive facial patches by the weight learning such that a domain-invariant feature representation involving micro-expression distinguishable information can be learned. Finally, we carry out extensive experiments to evaluate the proposed JPMM method is superior to recent state-of-the-art unsupervised DA methods in dealing with cross-domain MER.
High-voltage gain zero-current switching push–pull resonant converter for small energy sources

This study presents a high-voltage gain zero-current switching (ZCS) push–pull resonant converter for small energy sources. The converter provides a high voltage from a 12 V DC battery via isolated transformer and full-bridge rectifier. The main switches of the push–pull and full-bridge diode rectifier operate under ZCS condition. The advantage of this technique is the use of leakage inductance for ZCS operation of the power switch and in designing the secondary side of a resonant tank. A prototype high-voltage gain push–pull resonant converter was built and operated at 110 kHz fixed switching frequency, 350 V DC output voltage, and 200 W output power to analyse the effect of parasitic junction capacitance of the full-bridge rectifier, which significantly affects the operating point of the resonant tank and the voltage. This study introduces the implementation and design using the data of a single diode to calculate the parameters. The simulation and experimental results verified the proposed and designed circuits. Both results agreed with the theoretical analysis.