Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Acoustic Emission Sources in Early Stages of Fatigue Process of Inconel 713LC

Inconel 713LC is low carbon variant of Inconel 713 nickel-based cast alloy. The biggest advantage of these alloys is their ability to resist a wide variety of operating conditions (corrosive environment, high temperature, high stresses). Main area of applications is aircraft, energetic, chemical and petrochemical industry etc. In many applications, components undergo cyclic stresses. This study presents results of acoustic emission response of Inconel 713LC during high-cycle fatigue testing. In comparison with low-cycle fatigue, stage of initiation of micro cracks is in high-cycle region much more significant and can take several tens of percent of whole fatigue life. This work is focused on comparison of selected parameters of acoustic emission signal in pre-initiation and initiation stage of fatigue crack creation. Signal data were specified by linear location technique, hence only signal from shallow notch was analysed. Acoustic emission signal was correlated with frequency of load reversals which is a function of specimen's rigidity (modulus). Acoustic emission hits with higher stress were detected in pre-initiation stage whereas initiation stage hits exhibited low stress. Acoustic emission signal measurements are supplemented by fractographic and metallographic analysis.
Spatial modelling integrating agricultural production , costs and hydrology for nitrogen policy assessments-a catchment apporach

Nutrient loads cause eutrophication, and the non-point characteristics of this pollution problem has been studied for decades. Efforts have been made to reduce nutrient loads and eutrophication in Europe, US and elsewhere, but additional actions are required to achieve good water quality aimed for in water quality policies. Spatial data describing the relationships between biophysical and hydrological factors and agricultural production have been used to develop an ecological-economic model of the non-point pollution and the spatial configuration of the costs to reduce the loads. The model has been developed to analyze the cost-effective choice of abatement measures taking the nonpoint and diffuse distribution of the loads of nitrogen to the sea into account. The model is a cost-minimization model at a fine spatial resolution which identifies spatial distributions of the costeffective implementation of abatement measures. The model is developed to analyze and compare the costs and effects of uniform regulation versus spatially differentiated implementation of abatement measures, as well as how model assumptions affect the model solutions. Both types of analyses are regarded important for the use of this type of models in policy advise.
Metaphor Identification with Paragraph and Word Vectorization: An Attention-Based Neural Approach

The current study investigates approaches to automatic metaphor identiﬁcation, the computational task of identifying whether a word or phrase in a portion of text is an instance of metaphor. In addition to using the Skip-Gram and Continuous Bag-of-Words algorithms for word-level feature extraction, the Paragraph Vector is utilized for obtaining sentence-level distributional information, being an extension to these two algorithms for blocks of text larger than the word level. With features extracted using the above models, the performance of several different neural network systems are compared against a baseline of logistic regression on the VU Amsterdam Metaphor Corpus, with results showing a signiﬁcant improvement and high success rates across the different models. This can be seen as strong evidence for the necessity of using state-of-the-art neural network architectures in supervised metaphor identiﬁcation, being able to pick up on the various latent patterns provided by the vector space model.
Large scale simulation of CCN networks

This work addresses the performance evaluation of Content Centric Networks (CCN). Focusing on a realistic YouTube- like catalog, we conduct a very thorough simulation study of the main system performance, consider several ingredients such as network topology, multi-path routing, content popularity, caching decisions and replacement policies. Summa- rizing our main results, we gather that (i) the impact of the topology is limited, (ii) multi-path routing may play against CCN efficiency, (iii) simple randomized policies perform almost as well as more complex ones, (iv) catalog and pop- ularity settings play by far the most crucial role above all. Hopefully, our thorough assessment of scenario parameters can assist and promote the cross-comparison in the research community - for which we also provide our CCN simulator as open source software.
Traffic Anomaly Detection via Perspective Map based on Spatial-temporal Information Matrix

Anomaly detection on the road traffic has vast application prospects in urban traffic management and road safety. Due to the impact of many factors such as weather, viewpoints and road conditions in the real-world traffic scene, anomaly detection still faces many challenges. There are many causes for vehicle anomalies, such as crashes, vehicle on fires and vehicle faults, which exhibits different unknown behaviors. In this paper, we propose an anomaly detection system that includes three modules: background modeling module, perspective detection module, and spatialtemporal matrix discriminating module. The background modeling analyses the traffic flow to obtain the road segmentation results, and the vehicle flow superposition is used to obtain the continuous stationary region. The perspective detection module gets the perspective map by the first detection result, through which the image is cropped to uniform scale for different vehicles and re-detection. Finally, we get all anomalies by constructing spatial-temporal information matrix with the detection results. Furthermore, all anomalies are merged through the non maximum suppression (NMS) and the re-identification model, including spatial and temporal dimensions. The experimental results show that our system is effective in the Track3 test-set of NVIDIA AI CITY 2019 CHALLENGE, which finally ranked first in the competition, with a 97.06% F1-score and 5.3058 root mean square error (RMSE).
A Systematic Review of Methodologies and Models for the Analysis and Management of Associative and Hierarchical Risk in SMEs

As a result of the growing dependence of information society on ICTs, the need to know the risks that can affect information is enormously increasing with the purpose of protecting it. This article shows advances in the identification and management of risks in ICTs, particularly in the case of SMEs, along with the first proposal of a methodology for management and analysis of the associative risk in SMEs taking into account not only internal risks derived from SMEs but also other external risks derived from other enterprises in the same sector or collaborating with them. Thus, we will obtain a high quality risk analysis at low cost using advanced concepts such as “associative algorithms” and “enterprise social networks”. In the era of globalization, SMEs no longer work as independent companies but share more and more services, even facilities, with other companies. Therefore, we cannot obtain an adequate risk analysis without considering the risks associated with these collaborations. In this article we present rhe results of a systematic review of methodologies and models for the analysis and management of associative and hierarchical risk in SMEs.
A Review on Electrostatic Micromirror

Micromirror is a very small mirror based on the principle of Micro Electro Mechanical Systems (MEMS). Micromirror application in areas like laser scanning displays, DLP Projection system and HDTV are realized usingMEMS technology. Electrostatic actuation is one of the simplest actuation method based upon repulsive forces between same charges and attractive forces for different charges and the most widely used structures for this mechanism are electrostatically controlled prestressed
DETERMINATION OF ENERGY AND PROTEIN REQUIREMENTS AND THEIR RATIO IN THE RAMBON DUCKS RATION AT GROWING PERIOD

Rambon Ducks are local laying ducks in Indonesia which are generally raised under extensive systems. However the decline of land availability, the duck rearing systems requires change from extensive to intensive systems. This study was aimed to determine the energy and protein requirement and their balance in the Rambon ducks ration at growing period. There were two experiments in the research. First to find the value of Efficiency Utilization of Protein (EUP) and requirement of energy and protein based the calculation from Scott et al. (1982), the second experiment to find energy-protein ratio (EPR) in the ration used Completely Randomized Design. There were six different metabolizable energy/protein ratio in rations as treatments; P1 (2200 kcal/kg/12%); P2 (2200 kcal/kg/14%); P3 (2500 kcal/kg/12%); P4 (2500 kcal/kg/14%); P5 (2800 kcal/kg/14%), and P6 (2800 kcal/kg/16%). Each treatment was replicated four times. The data was analyzed using analysis of variance and the difference among treatments was analyzed by Duncan Test. The parameters measured were EUP, Energy and protein requirement, EPR, feed consumption, body weight gain and feed conversion. The result of the research show that the value of EUV of Rambon female duck at growing period is 57.76%, requirement of protein is 10,62 g/day and energy is 199.73 kcal/day, feed consumption 91.8 g/day. The conclusion that Energy-Protein Ratio in the ration 2200 kcal/kg/12% P (183.33) is enough for Rambon Ducks at growing period.
Learning Personal Tastes in Choosing Fashion Outfits

With the emergence of fashion recommendation, many researchers have attempted to recommend fashion items that fit consumers' tastes. However, few have looked into fashion outfits as a whole when making recommendations. In this paper, we propose a neural network that learns one's fashion taste and predicts whether an individual likes a fashion outfit. To improve learning, we also develop a fashion outfit negative sampling scheme to sample fashion outfits that are different enough. With experiments on the collected Polyvore dataset, we find that using complete images of fashion outfits performs well when learning individuals' tastes toward fashion outfits. Our proposed negative sampling scheme also improves the model's performance significantly, compared to random negative sampling.
Dispersion, sedimentation and aggregation of multi-walled carbon nanotubes as affected by single and binary mixed surfactants

Two commonly used dispersants, octyl phenol ethoxylate (Triton X-100) and sodium dodecyl sulfate (SDS), were employed to explore the effects of single or mixed surfactants on the dispersion, sedimentation and aggregation of multi-walled carbon nanotubes (MWCNTs). Non-ionic surfactant TX100 showed much superior capability to anionic surfactant SDS in dispersing MWCNTs due to the benzene ring structure in its tail group. The addition of SDS reduced the adsorption of TX100 on the surface of MWCNTs and the consequent suspension of MWCNTs. The dispersing ability of TX100–SDS binary mixture was between those of individual SDS and TX100. The introduction of SDS greatly retarded the sedimentation and aggregation of suspended MWCNTs. The critical coagulation concentration (CCC) values of suspended MWCNTs dispersed by TX100 (2000 mg l−1), SDS (2000 mg l−1) and TX100–SDS (2000 mg l−1 of each component) were 48.6, 398 and 324 mM, respectively, for Na+ treatments. The CCC values were much lower for Ca2+ treatments, which were 30.4 and 32.1 mM, respectively, for MWCNTs dispersed by TX100 and TX100–SDS mixture. Overall, these results demonstrated that although the introduction of SDS did not improve the ability of TX100 in suspending MWCNTs, the suspensions exhibited more stable properties than those dispersed by TX100 alone. Our findings have important implications for the design of surfactant mixtures and the prediction of the behaviour and fate of MWCNTs in the water environment.
An individual-based mechanical model of cell movement in heterogeneous tissues and its coarse-grained approximation

Mechanical heterogeneity in biological tissues, in particular stiffness, can be used to distinguish between healthy and diseased states. However, it is often difficult to explore relationships between cellular-level properties and tissue-level outcomes when biological experiments are performed at a single scale only. To overcome this difficulty we develop a multi-scale mathematical model which provides a clear framework to explore these connections across biological scales. Starting with an individual-based mechanical model of cell movement, we subsequently derive a novel coarse-grained system of partial differential equations governing the evolution of the cell density due to heterogeneous cellular properties. We demonstrate that solutions of the individual-based model converge to numerical solutions of the coarse-grained model, for both slowly-varying-in-space and rapidly-varying-in-space cellular properties. Applications of the model are discussed, including determining relative cellular-level properties and an interpretation of data from a breast cancer detection experiment.
Supervised Determined Source Separation with Multichannel Variational Autoencoder

This letter proposes a multichannel source separation technique, the multichannel variational autoencoder (MVAE) method, which uses a conditional VAE (CVAE) to model and estimate the power spectrograms of the sources in a mixture. By training the CVAE using the spectrograms of training examples with source-class labels, we can use the trained decoder distribution as a universal generative model capable of generating spectrograms conditioned on a specified class index. By treating the latent space variables and the class index as the unknown parameters of this generative model, we can develop a convergence-guaranteed algorithm for supervised determined source separation that consists of iteratively estimating the power spectrograms of the underlying sources, as well as the separation matrices. In experimental evaluations, our MVAE produced better separation performance than a baseline method.
Off-Court Generic Perceptual-Cognitive Training in Elite Volleyball Athletes: Task-Specific Effects and Levels of Transfer

Background: The nature of perceptual-cognitive expertise in interactive sports has gained more and more scientific interest over the last two decades. Research to understand how this expertise can be developed has not been addressed profoundly yet. In approaches to study this with interventional designs, only few studies have scrutinized several levels of transfer such as to the field. Therefore, the aim of this study was to examine the efficacy of a generic off-court perceptual-cognitive training in elite volleyball players on three different levels: task-specific, near-transfer, and far-transfer effects. Based on overlapping cognitive processes between training and testing, we hypothesized task-specific improvements as well as positive near- and far-transfer effects after a multiple-object tracking training intervention. Methods: Twenty-two volleyball experts completed a 8-week three-dimensional (3D) multiple-object tracking (3D-MOT) training intervention. A control group (n = 21; volleyball experts also) participated in regular ball practice only. Before and after training, both groups performed tests on the 3D-MOT, four near-transfer tests in cognitive domains, and a far-transfer, lab-based, and volleyball-specific blocking test. Results: The results of the 2 × 2 analysis of variance (ANOVA) (group, time) showed significant interaction effects in the 3D-MOT task [F(1,40) = 93.10; p < 0.001; ηp2 = 0.70] and in two near-transfer tests [sustained attention: F(1,40) = 15.45; p < 0.001; ηp2 = 0.28; processing speed: F(1,40) = 12.15; p = 0.001; ηp2 = 0.23]. No significant interaction effects were found in the far-transfer volleyball test. Conclusions: Our study suggests positive effects in task-specific and two near-transfer tests of a perceptual-cognitive intervention in elite volleyball athletes. This supports a partial overlap in cognitive processing between practice and tests with the result of positive near-transfer. However, there are no significant effects in far-transfer testing. Although these current results are promising, it is still unclear how far-transfer effects of a generic perceptual-cognitive training intervention can be assured.
Changes in the Hematological Variables in Pigs Supplemented With Yeast Cell Wall in Response to a Salmonella Challenge in Weaned Pigs

Stressors experienced by pigs at weaning may negatively impact health and productivity. Thus, supplements that enhance pig immunity during the early post-weaned period are of great interest to the swine industry. The objective of this experiment was to evaluate the performance and hematological responses of weaned pigs supplemented with yeast cell wall (YCW) when challenged orally with Salmonella Typhimurium. Weaned pigs were assigned to one of three treatments for 22d (n = 13/treatment): Control diet, which was a non-medicated starter diet (Control); Control diet supplemented with YCW at 250 mg/kg BW (YCW250; Phileo Lesaffre Animal Care, Milwaukee, Wisconsin, USA); and Control diet supplemented with YCW at 500 mg/kg BW (YCW500). On d19 blood samples were collected from −6 to 72 h relative to oral Salmonella Typhimurium (1 × 106 cfu/pig) challenge. Gain:feed was greater (P = 0.01) in YCW250 treatment compared to both Control and YCW500 pigs. Baseline intraperitoneal temperature was greater (P < 0.001) in YCW250 pigs than Control or YCW500 pigs. There was a treatment x time interaction for the change in intraperitoneal temperature (P < 0.01), post-challenge cortisol, white blood cell counts (WBC), neutrophils, and neutrophil:lymphocyte ratio (P ≤ 0.03). Control pigs had greater (P < 0.05) cortisol concentrations than both YCW-supplemented groups at 0 h, but Control pigs had reduced (P < 0.05) cortisol compared to YCW500 pigs at 24 and 30 h post-challenge. Control pigs had greater (P < 0.05) WBC counts than both YCW-supplemented groups 6 and 12 h post-challenge, and YCW250 pigs had reduced (P < 0.01) WBC counts than Control and YCW500 pigs 18 h post-challenge. Neutrophil counts were greater (P < 0.05) in Control pigs than both YCW-supplemented groups at 6 and 12 h post-challenge and were greater (P = 0.02) than YCW250 pigs at 18 h post-challenge. Lymphocytes were greater (P < 0.001) in Control and YCW500 pigs pre- and post-challenge compared to YCW250 pigs. Control pigs had the greatest (P < 0.001) monocyte counts compared to YCW treatments. There was no effect of yeast supplementation on fecal shedding or Salmonella counts in the rectum, colon or cecum (P ≥ 0.05). While some differences were observed in intraperitoneal temperature and some hematological variables, data suggests there were minimal effects of yeast supplementation on the acute immune response to Salmonella challenge.
Distinct Functional Contributions by the Conserved Domains of the Malaria Parasite Alveolin IMC1h

Invasive, motile life cycle stages (zoites) of apicomplexan parasites possess a cortical membrane skeleton composed of intermediate filaments with roles in zoite morphogenesis, tensile strength and motility. Its building blocks include a family of proteins called alveolins that are characterized by conserved “alveolin” domains composed of tandem repeat sequences. A subset of alveolins possess additional conserved domains that are structurally unrelated and the roles of which remain unclear. In this structure-function analysis we investigated the functional contributions of the “alveolin” vs. “non-alveolin” domains of IMC1h, a protein expressed in the ookinete and sporozoite life cycle stages of malaria parasites and essential for parasite transmission. Using allelic replacement in Plasmodium berghei, we show that the alveolin domain is responsible for targeting IMC1h to the membrane skeleton and, consequently, its deletion from the protein results in loss of function manifested by abnormally-shaped ookinetes and sporozoites with reduced tensile strength, motility and infectivity. Conversely, IMC1h lacking its non-alveolin conserved domain is correctly targeted and can facilitate tensile strength but not motility. Our findings support the concept that the alveolin module contains the properties for filament formation, and show for the first time that tensile strength makes an important contribution to zoite infectivity. The data furthermore provide new insight into the underlying molecular mechanisms of motility, indicating that tensile strength is mechanistically uncoupled from locomotion, and pointing to a role of the non-alveolin domain in the motility-enhancing properties of IMC1h possibly by engaging with the locomotion apparatus.
A Non-linear Association Between Total Small Vessel Disease Score and Hemorrhagic Transformation After Ischemic Stroke With Atrial Fibrillation and/or Rheumatic Heart Disease

Background: Previous studies have investigated the association between a single marker of cerebral small vessel disease (SVD) and hemorrhagic transformation (HT). However, the effect of the total SVD burden on HT has not been evaluated yet. We aimed to investigate the association between the total SVD score and HT in ischemic stroke patients with atrial fibrillation (AF) and/or rheumatic heart disease (RHD). Methods: Ischemic stroke patients with AF and/or RHD admitted within 7 days after onset were enrolled at two hospitals in China. The total SVD score was based on the presence of lacunes, extensive white matter hyperintensities, cerebral microbleeds, and moderate to severe enlarged perivascular spaces in the basal ganglia. One point was awarded for the presence of each marker, with the total SVD score ranging from 0 to 4 points. HT was assessed based on follow-up imaging scans during hospitalization and was classified according to the radiographic appearance and associated neurological deterioration. Results: Of 207 enrolled patients (mean age, 67.79 years; 58.9% female), 89 (43.0%) developed HT. The distribution of the total SVD score was significantly different between patients with and without HT in the univariate analysis (p = 0.04). After adjustment for confounders, a SVD score of 1 was independently associated with an increased risk of HT [odds ratio (OR), 3.23; 95% confidence interval (CI), 1.48–7.04; p = 0.003], while a SVD score ≥2 was inversely related to the occurrence of HT (OR, 0.41; 95% CI, 0.19–0.91; p = 0.03). These independent associations remained significant in the subgroups of hemorrhagic infarction and asymptomatic HT (all p < 0.05). Conclusions: In our study, the relationship between the total SVD score and HT was not linear, since the presence of only one marker of SVD was associated with an increased risk of HT, while the presence of two or more markers of SVD was a potential protective factor for HT. These results indicate the need to take the total SVD score into account, not only a single SVD marker, when assessing the risk of HT. Further studies with larger samples are required to validate these findings.