Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel bearing fault diagnosis method based on 2D image representation and transfer learning-convolutional neural network

Traditional methods used for intelligent condition monitoring and diagnosis significantly depend on manual feature extraction and selection. To address this issue, a transfer learning-convolutional neural network (TLCNN) based on AlexNet is proposed for bearing fault diagnosis. Firstly, a 2D image representation method converts vibration signals to 2D time-frequency images. Secondly, the proposed TLCNN model extracts the features of the 2D time-frequency images and achieves the classification conditions of the bearing, which is faster to train and more accurate. Thirdly, t-distributed stochastic neighbor embedding (t-SNE) is applied to visualize the feature learning process to demonstrate the feature learning ability of the proposed model. The experimental results verify that the proposed fault diagnosis model has higher accuracy and has much better robustness against noise than other deep learning and traditional methods.
Umbrella systematic review of potential quality indicators for the detection of dysplasia and cancer at upper gastrointestinal endoscopy

Abstract Background and study aims Upper gastrointestinal (UGI) endoscopy lacks established quality indicators. We conducted an umbrella systematic review of potential quality indicators for the detection of UGI cancer and dysplasia. Methods Bibliographic databases were searched up to December 2021 for systematic reviews and primary studies. Studies reporting diagnostic accuracy, detection rates or the association of endoscopy or endoscopist-related factors with UGI cancer or dysplasia detection were included. AMSTAR2 and JBI checklists were used to assess systematic review and primary study quality. Clinical heterogeneity precluded meta-analysis and findings are summarized narratively. Results Eight systematic reviews and nine primary studies were included. Image enhancement, especially narrow band imaging, had high diagnostic accuracy for dysplasia and early gastric cancer (pooled sensitivity 0.87 (95% CI 0.84–0.89) and specificity 0.97 (0.97–0.98)). Higher detection rates with longer endoscopy examination times were reported in three studies, but no difference was observed in one study. Endoscopist biopsy rate was associated with increased gastric cancer detection (odds ratio 2.5; 95% confidence interval [CI] 2.1–2.9). Early esophageal cancer (0.17% vs 0.14%, P =0.04) and gastric cancer (0.16% vs 0.12%, P =0.02) detection rates were higher with propofol sedation compared to no sedation. Endoscopies performed by trained endoscopists on dedicated Barrett’s surveillance lists had higher detection rates (8% vs 3%, P <0.001). The neoplasia detection rate during diagnostic endoscopies for Barrett’s esophagus was 7% (95% CI 4%-10%). Conclusions Image enhancement use, longer examination times, biopsy rate and propofol sedation are potential quality indicators for UGI endoscopy. Neoplasia detection rate and dedicated endoscopy lists are additional potential quality indicators for Barrett’s esophagus
Single-center experience of endovascular treatment for patients with progressive posterior circulation cerebral infarction exceeding 24 h

Abstract Background Evidence of endovascular treatment (ET) for patients with progressive infarction of the posterior circulation exceeding 24 h is lacking. Objective To evaluate the efficacy and safety of ET for progressive posterior circulation cerebral infarction. Methods This retrospective study evaluated the ET for 18 patients with posterior circulation infarction caused by vertebrobasilar artery occlusion from July 2017 to November 2018. The conditions of patients worsened despite receiving intravenous thrombolysis or combination therapy with clopidogrel and aspirin. The time from the onset of cerebral infarction to puncture was >24 h. The preoperative National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), and related risk factors of patients at 3 months were analyzed postoperatively. Results The preoperative NIHSS score was 10.6 (IQR: 6.5), and the time from onset to puncture was 163.5 ± 144.7 h. Postoperative blood flow was modified thrombolysis in cerebral infarction (mTICI) grade 2b or above. During the follow-up period, 1 patient died of basilar artery re-occlusion and pulmonary infection, and 1 died of postoperative hyperperfusion hemorrhage, with a mortality rate of 11.1% (2/18). No recurrent ischemic events were observed in any of the 16 patients during the 3-month follow-up period. The mean mRS score was 1.3 (IQR: 2.3), and 75% patients (12/16) had an mRS score of 0–2. There were no significant differences in age, gender, clinical characteristics, and stroke subtype between patients with mRS scores ≤2 and >2. Conclusion In patients with progressive posterior circulation cerebral infarction caused by vertebral basilar artery occlusion, ET is effective and safe even if the time from onset to puncture exceeds 24 h.
International Journal of Cybersecurity Intelligence & Cybercrime International Journal of Cybersecurity Intelligence & Cybercrime

: Online communications are ever increasing, and we are constantly faced with the challenge of whether online information is credible or not. Being able to assess the credibility of others was once the work solely of intelligence agencies. In the current times of disinfor-mation and misinformation, understanding what we are reading and to who we are paying attention to is essential for us to make considered, informed, and accurate decisions, and it has become everyone’s business. This paper employs a literature review to examine the empirical evidence across online credibility, trust, deception, and fraud detection in an effort to consolidate this information to understand adversary online credibility – how do we know with whom we are conversing is who they say they are? Based on this review, we propose a model that includes examining information as well as user and interaction characteristics to best inform an assessment of online credibility. Limitations and future opportunities are highlighted.
Analyse expérimentale d'un jet turbulent impactant sur un plaque plane et sur un obstacle de section carrée

Cette etude aborde l'impact d'un jet sur une plaque plane et sur un obstacle de section carree. L'objectif de ce travail est l'analyse experimentale de l'ecoulement, et du transfert de chaleur associe, lorsque la surface est chauffee a densite de flux constante. Les mesures de vitesse et de turbulence ont ete menees par la Velocimetrie par Images des Particules (PIV) et l'anemometrie a fil chaud, ce qui a permis la mesure de chaque composante et du champ complet en particulier au voisinage des parois. Differents post-traitements de la PIV ont permis une nette amelioration de l'evaluation des fluctuations de vitesse. Les mesures de la temperature ont ete effectuees par la thermographie infrarouge et la thermometrie a fil froid. La camera utilisee, de technologie avancee, possede une resolution thermique tres faible. Un travail important de post traitement des images infrarouge a permis de quantifier le champ de coefficient d'echange avec une precision inferieure a 5%. Plusieurs corrections de la temperature ont ete menees sur les mesures par la thermometrie a fil froid pour tenir compte des effets inertiel et de conduction au niveau de la sonde. Les mesures concernant l'impact d'un jet sur une plaque plane ont complete les donnees de la litterature tout en mettant en evidence quelques desaccords. Nous proposons une analyse qui permet d'expliquer l'effet de la distance d'impact sur le coefficient de transfert de chaleur local. Ce travail represente une base de donnees aerothermiques coherente pour la validation des modeles de turbulence. L'impact du jet sur un barreau a section carree a montre plusieurs structures d'ecoulement 3D interessantes et une distribution complexe du coefficient de transfert de chaleur associee. Les phenomenes de decollement et de recirculation 3D ont ete identifies et analyses. Egalement, l'influence de la position du jet par rapport au barreau sur la topologie de l'ecoulement a ete clairement mise en evidence.
Journal of A ﬀ ective Disorders

Background: Jealousy is a heterogenous emotion on a spectrum from normality to psychopathology. The relationship between di ﬀ erent jealousy subtypes/dimensions and a ﬀ ective temperaments remain unknown. In addition, few large surveys have investigated the associations between jealousy subtypes and psychopathological dimensions. Methods: A Brazilian Portuguese version of the “ Questionario della Gelosia ” (QUEGE) was developed. We obtained data from an anonymous web-based research platform. Socio-demographic data was obtained and participants answered the QUEGE, the TEMPS-Rio de Janeiro, and the Symptom Checklist-90-Revised (SCL-90-R). Results: 2042 participants (29% men, 71% female, mean age+SD: 28.9±8.8 years), took part in this survey. Con ﬁ rmatory factor analysis provided a ﬁ ve-factor model for the QUEGE with self-esteem, paranoia, interpersonal sensitivity, fear of being abandoned, and obsessive dimensions. The anxious, irritable, cyclothymic, and depressive temperaments were independently associated with jealousy dimensions, whereas the hyperthymic temperament was associated with lower scores on the self-esteem jealousy dimension ( N =2042, P <0.001). Jealousy subtypes were dissimilarly associated with SCL-90R psychopathological dimensions, whereas the ‘ obsessive ’ jealousy dimension was not signi ﬁ cantly associated with SCL-90R dimension scores. We found no independent in ﬂ uence of gender across any jealousy dimension. Limitations: A convenience web-based sample was employed. Cross-sectional design precludes the establishment of causal inferences. Conclusions: Our data indicate that a ﬁ ve-factor solution may provide the best-ﬁ t model for the QUEGE. Di ﬀ erent jealousy subtypes were independently associated with a ﬀ ective temperaments and psychopathological dimensions
Preparing Students for Extension Careers and Expanding U.S. Extension Reach Through International Service Learning

As U.S. Extension broadens its reach around the globe, an increased need exists for Extension professionals who have not only technical knowledge but also the cultural competencies to apply that knowledge in international settings. We describe a course that provides students with the opportunity to develop skills needed for potential careers in Extension, especially those involving international focuses, while advancing U.S. Extension's international efforts. The course also may serve as a model for instructors wishing to integrate Extension concepts into their teaching of undergraduates, thereby preparing individuals to make immediate impacts in Extension careers.
Use of Precedent and Antecedent Information in Strategic Cost Use of Precedent and Antecedent Information in Strategic Cost Management Management

Integral to strategic cost management is the choice of procuring ﬂ exible versus committed resources conditioned on demand uncertainty. Prior research shows that costs respond less to decreases than increases in sales activity when ﬁ rms invest in committed resources. We analyze asymmetry in cost behavior to investigate how resource procurement decisions between ﬂ exible and committed resources are related to precedent and antecedent information about demand uncertainty. We ﬁ nd that the asymmetry of cost responsiveness increases with historical sales growth and with the ﬁ rm's market-to-book ratio, and decreases with historical sales volatility. We ﬁ nd similar results for ﬁ rm-speci ﬁ c deviations of sales growth, sales volatility and the market-to-book ratio from the industry averages. These results illustrate how managers might combine precedent and antecedent information in formulating a resource procurement plan as a means of strategic cost management.
Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical Study

Evaluating the quality of generated text is a challenging task in NLP, due to the inherent complexity and diversity of text. Recently, large language models (LLMs) have garnered significant attention due to their impressive performance in various tasks. Therefore, we present this paper to investigate the effectiveness of LLMs, especially ChatGPT, and explore ways to optimize their use in assessing text quality. We compared three kinds of reference-free evaluation methods. The experimental results prove that ChatGPT is capable of evaluating text quality effectively from various perspectives without reference and demonstrates superior performance than most existing automatic metrics. In particular, the Explicit Score, which utilizes ChatGPT to generate a numeric score measuring text quality, is the most effective and reliable method among the three exploited approaches. However, directly comparing the quality of two texts may lead to suboptimal results. We believe this paper will provide valuable insights for evaluating text quality with LLMs and have released the used data.
Antiferromagnetism of the cation-ordered warwickite system Mn 2-x Mg x BO 4

: X-ray diffraction, heat capacity and magnetic measurements are performed on single crystals of Mn 2-x Mg x BO 4 ( x = 0.55, 0.63 or 0.67) with the warwickite structure. The monoclinic symmetry is found for all samples with the space group P121/n1. The M1 site is occupied by trivalent Mn ions while the M2 site is occupied by a mixture of divalent Mg and Mn ions. Regular cation and charge distributions are observed, which is unusual for heterometallic warwickites. The local octahedral distortions of M1O 6 show the monotonic dependence on the Mg content and are in accordance with the Jahn-Teller distortion. All samples are found to undergo long-range antiferromagnetic ordering with rather low transition temperatures of T N = 16, 14 and 13 K for x =0.55, 0.63, and 0.67, respectively. The ordering of local octahedral distortions, caused by the strong electron-phonon interaction of the trivalent Mn ions, is proposed to stabilise the cationic ordering and, as a result, the long-range magnetic ordering in the material.
Cultural identity through an educational school trip: voices of indigenous Papuan students

Educational school trips may contribute to student visitors' cultural identity by facilitating exposure to new cultural values. This study sought to analyse how indigenous Papuan student visitors from a secondary school in Indonesia make meaning of their own cultural identity, and further, explore their responses to the cultural issues faced by young Papuan generations. The study employed a grounded qualitative methodology, which allowed respondents to voice their own opinions on cultural identity. The results include 3 themes: Becoming more Papuan; Clarifying and understanding the cultural context and; Self-reflection. This study reveals how students in the trips conceptualize cultural understanding as a bridge to their cultural identity. Furthermore, they brought the larger ideas of Papuan identity and community values and demonstrated intention to maintain it through conservation and preservation. Several recommendations are provided for future research in the tourism and education fields to foster cultural experiences for student visitors from different cultural backgrounds.
Recover Glacier Velocity Fields Derived From the SAR Speckle Tracking Technique Using Artificial Neural Network

The speckle tracking technique has demonstrated its great potential in glacier velocity field (GVF) mapping applications. It analyzes the cross correlation between two synthetic aperture radar (SAR) images, which is capable of providing 2-D glacier motion measurements with acceptable accuracy. Since the coherence between a SAR image pair illuminating glacier areas cannot be preserved everywhere in nearly all cases, inevitable no data areas will be presented in SAR speckle tracking products. In this letter, a relatively convenient method is proposed to recover a GVF generated by the speckle tracking technique. This method considers a GVF recovery problem to be a unitary supervised training problem and resolve it via an artificial neural network. A targeted architecture of the network for recovering a GVF is presented. Moreover, the parameters correlative with glacier motion mechanism are proposed to be introduced into the network, which is able to effectively improve the performance of GVF recovery. For the purpose of validation, the proposed method is compared with the well-known Kriging interpolation method based on real speckle tracking products. The experimental results demonstrate that the proposed method can effectively recover a GVF derived from the speckle tracking technique.
assessment of

In analyzing repeated measurements from randomized controlled trials with mixed-effects models, it is important to carefully examine the conventional normality assumption regarding the random-effects distribution and its dependence on treatment allocation in order to avoid biased estimation and correctly interpret the estimated random-effects distribution. In this paper, we propose the use of a gradient function method in modeling with the different random-effects distributions depending on the treatment allocation. This method can be effective for considering in advance whether a proper fit requires a model that allows dependence of the random-effects distribution on covariates, or for finding the subpopulations in the random effects.
Applied Catalysis B: Environmental

Low loading PtAu nanoparticles supported on high area carbon were synthesized by water-in-oil microemulsion method and examined for formic acid and methanol oxidation. Prepared catalyst powder was characterized by X-ray di ﬀ raction (XRD), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS). These techniques revealed that the catalyst contains rather agglom-erated quasi-spherical particles, ∼ 4 nm diameter, composed of a solid solution of Pt and Au with only ∼ 4 at% of Au. In spite of such low Au content, both onset and peak potentials for CO oxidation are shifted some 150mV to more positive values in comparison to Pt synthesized in the same manner due to stronger binding of CO as a result of notable electronic e ﬀ ect. It is important that this small quantity of Au also signi ﬁ cantly in ﬂ uences oxidation of formic acid promoting direct path and suppressing indirect path in formic acid oxidation in a degree as expected by a much larger quantity of Au. Such improvement could be due exclusively by ensemble e ﬀ ect of high number of small Pt domains which formation could be possible only by very ﬁ ne dispersion of such low Au quantity. High number of small Pt domains is corroborated by lower activity for methanol oxidation in comparison to Pt catalyst synthesized by the same procedure. These results emphasize the importance of the Au dispersion on the surface of Pt over its quantity in PtAu catalyst with regards to both, the ensemble and the electronic e ﬀ ects.
A learning approach to swarm-based path detection and tracking

This dissertation presents a set of top-down modulation mechanisms for the modulation of the swarm-based visual saliency computation process proposed by Santana et al. (2010) in context of path detection and tracking. In the original visual saliency computation process, two swarms of agents sensitive to bottom-up conspicuity information interact via pheromone-like signals so as to converge on the most likely location of the path being sought. The behaviours ruling the agents’ motion are composed of a set of perception-action rules that embed top-down knowledge about the path’s overall layout. This reduces ambiguity in the face of distractors. However, distractors with a shape similar to the one of the path being sought can still misguide the system. To mitigate this issue, this dissertation proposes the use of a contrast model to modulate the conspicuity computation and the use of an appearance model to modulate the pheromone deployment. Given the heterogeneity of the paths, these models are learnt online. Using in a modulation context and not in a direct image processing, the complexity of these models can be reduced without hampering robustness. The result is a system computationally parsimonious with a work frequency of 20 Hz. Experimental results obtained from a data set encompassing 39 diverse videos show the ability of the proposed model to localise the path in 98.67 % of the 29789 evaluated frames. keywords: swarm cognition, monocular path detection, visual saliency, bio-inspired methods, off-road navigation.
Triangle Counting Through Cover-Edges

Counting and finding triangles in graphs is often used in real-world analytics to characterize cohesiveness and identify communities in graphs. In this paper, we propose the novel concept of a cover-edge set that can be used to find triangles more efficiently. We use a breadth-first search (BFS) to quickly generate a compact cover-edge set. Novel sequential and parallel triangle counting algorithms are presented that employ cover-edge sets. The sequential algorithm avoids unnecessary triangle-checking operations, and the parallel algorithm is communication-efficient. The parallel algorithm can asymptotically reduce communication on massive graphs such as from real social networks and synthetic graphs from the Graph500 Benchmark. In our estimate from massive-scale Graph500 graphs, our new parallel algorithm can reduce the communication on a scale 36 graph by 1156x and on a scale 42 graph by 2368x.
The challenge of identifying and conserving valuable ecosystems close to human settlements in a northern area.An approach based on field- and satellite data.

The rich broadleaved forests of North Norway have high species diversity. Mappings of biodiversity have been undertaken in the two municipalities Malselv and Bardu, but these mappings are far from exhaustive. This study examines classification methods for mapping rich broadleaved forests with the use of Landsat ETM+ images, and with vegetation indices as ancillary data. Three classifications were made; one supervised (on a July image) and two unsupervised (on the July image and a September image). Of these, the unsupervised classification of the July image had the best Overall Accuracy at 60.59 % and a Kappa coefficient of 0.4262. It seems that it is somewhat difficult to differentiate between the various rich broadleaved forest types with the use of Landsat ETM+ images, with their medium resolution, and a per-pixel classification. But with the added use of a tresholded NDVI it is possible to discern richer forest types in the study area, and to some degree imply what kind of forest we might expect to find based on the best classifications. I have compared my findings with the earlier biodiversity maps, and on this background I suggest that a new, and more thorough, mapping of the region is carried out.