bluuebunny/crossref_metadata_2025 huggingface dataset:
Youth Work in Europa
Authors: Münderlein Regina , Autor Jana
Published: July 2022

Jugendarbeit ist nicht nur in Deutschland von Bedeutung. Im europäischen Raum hat sich in den letzten 10 Jahren ein neues jugendpolitisches Verständnis von „Youth Work“, dem englischen Begriff für Jugendarbeit und Jugendsozialarbeit, entwickelt. Dies geht einher mit vielen spannenden neuen Möglichkeiten. Nur: was genau ist unter „Youth Work“ zu verstehen? Neben einem detaillierten Überblick über die bereits existierenden jugendpolitischen Strukturen der Europäischen Union und des Europarates für die Jugendarbeit wird in diesem Informationsband auch das Engagement der „Community of Practice“ (d.h. der Gruppe aller Menschen, die in und für Jugendarbeit aktiv sind), verdeutlicht. Die übersichtlichen Informationen sind kompakt gefasst und zielen darauf ab, jungen Menschen, Fachkräften der Jugendarbeit und allen Interessierten neue Möglichkeiten der (Mit-)Gestaltung in der europäischen Youth Work aufzuzeigen.
Symbolic knowledge extraction from opaque ML predictors in PSyKE: Platform design & experiments
Authors: Sabbatini Federico , Ciatto Giovanni , Calegari Roberta , Omicini Andrea
Published: July 2022

A common practice in modern explainable AI is to post-hoc explain black-box machine learning (ML) predictors – such as neural networks – by extracting symbolic knowledge out of them, in the form of either rule lists or decision trees. By acting as a surrogate model, the extracted knowledge aims at revealing the inner working of the black box, thus enabling its inspection, representation, and explanation. Various knowledge-extraction algorithms have been presented in the literature so far. Unfortunately, running implementations of most of them are currently either proofs of concept or unavailable. In any case, a unified, coherent software framework supporting them all – as well as their interchange, comparison, and exploitation in arbitrary ML workflows – is currently missing. Accordingly, in this paper we discuss the design of PSyKE, a platform providing general-purpose support to symbolic knowledge extraction from different sorts of black-box predictors via many extraction algorithms. Notably, PSyKE targets symbolic knowledge in logic form, allowing the extraction of first-order logic clauses. The extracted knowledge is thus both machine- and human-interpretable, and can be used as a starting point for further symbolic processing—e.g. automated reasoning.
Linguistic and semantic layers for emergency plans
Authors: Cossentino Massimo , Guastella Davide , Lopes Salvatore , Sabatucci Luca , Tripiciano Mario
Published: July 2022

Plans for emergency response are complex collaborations in which actors take roles and responsibilities. They are generally long textual documents containing practical instructions, in natural language, for hazard responses. A more rigorous structured-text would be useful for a twofold audience. From one side, it can be useful for quickly understanding the plan and on the other side it can be used to improve the modelling phase and delivering an automatic emergency-support system. This paper proposes an approach, conceived for humans, for converting a free-form plan document into a structured version of the same document. The approach is based on a linguistic and semantic analysis that are strictly correlated and materialize in a metamodel. It contains the essential elements of an emergency plan, and it aids in interpreting the input document also reducing inconsistencies, redundancies, and ambiguities.
Risk sensitive scheduling strategies of production studios on the US movie market: An agent-based simulation
Authors: Bertolotti Francesco , Roman Sabin
Published: July 2022

The movie industry is a highly differentiated context where production studios compete in non-price product attributes, which influences the box office results of a motion picture. Because of the short life cycle and the constant entrance of new competitive products, temporal decisions play a crucial role. Time series of the number of movies on release and the sum of the box office results of the ten top motion pictures (ranked by box office result for that week) present a counterphased seasonality in the US movie market. We suggest that a possible reason is a risk sensitivity adaptation in the behaviour of the movie’s distributors. This paper provides a model supporting this hypothesis. We developed an agent-based model of a movie market, and we simulated it for 15 years. A comparable global behaviour exists when producers schedule the movies according to given risk-sensitive strategies. This research improves the knowledge of the US motion picture market, analyzing a real-world scenario and providing insight into the behaviour of existing firms in a complex environment.
A comparison of declarative AI techniques for computer automated design of elevator systems
Authors: Cicala G. , Demarchi S. , Menapace M. , Annunziata L. , Tacchella A.
Published: July 2022

Like other custom-built machinery, elevators are charecterized by a design process which includes selection, sizing and placement of components to fit a given configuration, satisfy users’ requirements and adhere to stringent normative regulations. Unlike mass-produced items, the design process needs to be repeated almost from scratch each time a new configuration is considered. Since elevators are still designed mostly manually, project engineers must engage in time-consuming and error-prone activities over and over again, leaving little to be reused from one design to the next. Computer automated design can provide a cost-effective solution as it relieves the project engineer from such burdens. However, it introduces new challenges both in terms of efficiency — the search space for solutions grows exponentially in the number of component choices — and effectiveness — the perceived quality of the final design may not be as good as in the manual process. In this paper we compare three mainstream AI techniques that can provide problem-solving capabilities inside our tool LiftCreate for automated elevator design, namely Genetic Algorithms (GAs), Constraint Programming (CP) and Satisfiability Modulo Theories (SMT). A special-purpose heuristic search technique embedded in LiftCreate provides us with a yardstick to evaluate the solutions obtained with GAs, CP and SMT and to assess their feasibility for practical applications.
Exploiting auto-encoders for explaining black-box classifiers
Authors: Guidotti Riccardo
Published: July 2022

Recent years have witnessed the rise of accurate but obscure classification models that hide the logic of their internal decision processes. In this paper, we present a framework to locally explain any type of black-box classifiers working on any data type through a rule-based model. In the literature already exists local explanation approaches able to accomplish this task. However, they suffer from a significant limitation that implies representing data as a binary vectors and constraining the local surrogate model to be trained on synthetic instances that are not representative of the real world. We overcome these deficiencies by using autoencoder-based approaches. The proposed framework first allows to generate synthetic instances in the latent feature space and learn a latent decision tree classifier. After that, it selects and decodes the synthetic instances respecting local decision rules. Independently from the data type under analysis, such synthetic instances belonging to different classes can unveil the reasons for the classification. Also, depending on the data type, they can be exploited to provide the most useful kind of explanation. Experiments show that the proposed framework advances the state-of-the-art towards a comprehensive and widely usable approach that is able to successfully guarantee various properties besides interpretability.
A Comparison of Operational Definitions for Mild Cognitive Impairment
Authors: Polcher Alexandra , Wolfsgruber Steffen , Peters Oliver , Frölich Lutz , Wiltfang Jens , Kornhuber Johannes , Hüll Michael , Rüther Eckart , Lewczuk Piotr , Maier Wolfgang , Jessen Frank , Wagner Michael
Published: July 2022

Background:

Consideration of many tests from different cognitive domains in defining mild cognitive impairment (MCI) is clinical routine, but guidelines for a neuropsychological operationalization of MCI are lacking.

Objective:

Among different operational MCI criteria, to identify those which are best in predicting either conversion to dementia, or a biomarker profile indicative for Alzheimer’s disease (AD).

Methods:

Memory clinic patients without dementia ( N = 558; mean age = 66; up to 3 years of follow-up; n = 360 with baseline CSF biomarkers) were included in an observational study using most liberal criteria of cognitive impairment. Four operational definitions of MCI were retrospectively applied: 1) amnestic MCI (CERAD word list delayed recall), 2) CERAD total score, 3) comprehensive criteria and 4) base rate corrected CERAD. We compared their accuracy in predicting incident all-cause dementia or AD dementia within three years, or a concurrent CSF Aβ42/tau-ratio indicative of AD.

Results:

The four definitions overlapped considerably, classified 35–58% of the original sample as impaired and were associated with markedly increased PPVs regarding incident all-cause dementia (39–46% versus 26% of the original sample), AD dementia and AD biomarker positivity. The base rate corrected MCI definition had the highest prognostic accuracy.

Conclusion:

he operational criteria examined seem suitable to specify MCI in memory clinic settings, as they identify subjects at high risk of clinical progression. Depending on the neuropsychological battery in use, one or several of these criteria could help to calibrate the clinical judgment of test results, reduce false-positive decisions, and define risk-enriched groups for clinical trials.
Polygenic Scores of Alzheimer’s Disease Risk Genes Add Only Modestly to APOE in Explaining Variation in Amyloid PET Burden
Authors: Ramanan Vijay K. , Heckman Michael G. , Przybelski Scott A. , Lesnick Timothy G. , Lowe Val J. , Graff-Radford Jonathan , Mielke M. , Jack Clifford R. , Knopman David S. , Petersen Ronald C. , Ross Owen A. , Vemuri Prashanthi ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: July 2022

Background:

Brain accumulation of amyloid-β is a hallmark event in Alzheimer’s disease (AD) whose underlying mechanisms are incompletely understood. Case-control genome-wide association studies have implicated numerous genetic variants in risk of clinically diagnosed AD dementia.

Objective:

To test for associations between case-control AD risk variants and amyloid PET burden in older adults, and to assess whether a polygenic measure encompassing these factors would account for a large proportion of the unexplained variance in amyloid PET levels in the wider population.

Methods:

We analyzed data from the Mayo Clinic Study of Aging (MCSA) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Global cortical amyloid PET burden was the primary outcome. The 38 gene variants from Wightman et al. (2021) were analyzed as predictors, with PRSice-2 used to assess the collective phenotypic variance explained.

Results:

Known AD risk variants in APOE, PICALM, CR1, and CLU were associated with amyloid PET levels. In aggregate, the AD risk variants were strongly associated with amyloid PET levels in the MCSA ( p = 1.51×10–50) and ADNI ( p = 3.21×10–64). However, in both cohorts the non- APOE variants uniquely contributed only modestly (MCSA = 2.1%, ADNI = 4.4%) to explaining variation in amyloid PET levels.

Conclusion:

Additional case-control AD risk variants added only modestly to APOE in accounting for individual variation in amyloid PET burden, results which were consistent across independent cohorts with distinct recruitment strategies and subject characteristics. Our findings suggest that advancing precision medicine for dementia may require integration of strategies complementing case-control approaches, including biomarker-specific genetic associations, gene-by-environment interactions, and markers of disease progression and heterogeneity.
Primary and Secondary Care Related Quality Indicators for Dementia Care Among Australian Aged Care Users: National Trends, Risk Factors, and Variation
Authors: Rahja Miia , Air Tracy , Ahern Susannah , Ward Stephanie A. , Caughey Gillian E. , Sluggett Janet K. , Cations Monica , Lin Xiaoping , Wallis Kasey , Crotty Maria , Inacio Maria C.
Published: July 2022

Background:

Studies related to clinical quality indicators (CQIs) in dementia have focused on hospitalizations, medication management, and safety. Less attention has been paid to indicators related to primary and secondary care.

Objective:

To evaluate the incidence of primary and secondary care CQIs for Australians with dementia using government-subsidized aged care. The examined CQIs were: comprehensive medication reviews, 75+ health assessments, comprehensive geriatric assessments, chronic disease management plans, general practitioner (GP) mental health treatment plans, and psychiatrist attendances.

Methods:

Retrospective cohort study (2011–2016) of 255,458 individuals. National trend analyses estimated incidence rates and 95% confidence intervals (CI) using Poisson or negative binomial regression. Associations were assessed using backward stepwise multivariate Poisson or negative binomial regression model, as appropriate. Funnel plots examined geographic and permanent residential aged care (PRAC) facility variation.

Results:

CQI incidence increased in all CQIs but medication reviews. For the overall cohort, 75+ health assessments increased from 1.07/1000 person-days to 1.16/1000 person-days (adjusted incidence rate ratio (aIRR) = 1.03, 95% CI 1.02–1.03).Comprehensive geriatric assessments increased from 0.24 to 0.37/1000 person-days (aIRR = 1.12, 95% CI 1.10–1.14). GP mental health treatment plans increased from 0.04 to 0.07/1000 person-days (aIRR = 1.13, 95% CI 1.12–1.15). Psychiatric attendances increased from 0.09 to 0.11/1000 person-days (aIRR = 1.05, 95% CI 1.03–1.07). Being female, older, having fewer comorbidities, and living outside a major city were associated with lower likelihood of using the services. Large geographical and PRAC facility variation was observed (0–92%).

Conclusion:

Better use of primary and secondary care services to address needs of individuals with dementia is urgently needed.
Facets of Personality and Risk of Cognitive Impairment: Longitudinal Findings in a Rural Community from Sardinia
Authors: Terracciano Antonio , Piras Maria Rita , Sutin Angelina R. , Delitala Alessandro , Curreli Nicolò Camillo , Balaci Lenuta , Marongiu Michele , Zhu Xianghe , Aschwanden Damaris , Luchetti Martina , Oppong Richard , Schlessinger David , Cucca Francesco , Launer Lenore J. , Fiorillo Edoardo
Published: July 2022

Background:

Few studies have examined the associations between personality facets and dementia risk and rarely included individuals from rural settings or with low education.

Objective:

To examine the association between personality and the risk of cognitive impairment.

Methods:

Participants (N = 1,668; age 50 to 94 at baseline; 56.4% women; 86.5% less than high school diploma) were from a rural region of Sardinia (Italy) who completed the Revised NEO Personality Inventory (NEO-PI-R) during the first wave (2001–2004) and the Mini-Mental State Examination (MMSE) at waves two to five (2005–2021). Cox regression was used to test personality and covariates as predictors of cognitive impairment based on MMSE education-adjusted cutoffs.

Results:

During the up to 18-year follow-up (M = 10.38; SD = 4.76), 187 individuals (11.2%) scored as cognitively impaired. Participants with higher neuroticism (particularly the depression facet [HR = 1.22, 95% CI = 1.06–1.40]), and lower agreeableness (particularly the modesty facet [HR = 0.83, 95% CI = 0.71–0.97]) and lower conscientiousness (particularly the dutifulness facet [HR = 0.78, 95% CI = 0.67–0.92]) were at higher risk of cognitive impairment. Lower warmth ([HR = 0.75, 95% CI = 0.65–0.87], facet of extraversion) and ideas ([HR = 0.76, 95% CI = 0.65–0.89], facet of openness) were also associated with increased risk of impairment. These associations were virtually unchanged in models that accounted for other risk factors, including smoking, depression, obesity, hypertension, diabetes, and apolipoprotein E ( APOE) ɛ4 carrier status. Across the five domains, sex and the APOE variant did not moderate the associations.

Conclusion:

In a sample with demographic characteristics underrepresented in dementia research, this study identifies personality domains and facets most relevant to the risk of cognitive impairment.
Fault tolerance analysis of double winding permanent magnet wind generator based on field circuit combination method
Authors: AI Mengmeng , Xu Ziyi , Liu Wenhui
Published: July 2022

Aiming at the problem that the reliability of traditional double winding permanent magnet wind generator is low when it runs on the sea, and it cannot run normally when the fault occurs, the fault tolerance characteristics of the generator are studied. Taking a 60 kW double winding permanent magnet synchronous wind generator as an example, the finite element method is used to calculate the electromagnetic parameters of the generator under rated load, single winding fault condition and fault-tolerant condition, and the variation characteristics of magnetic density, electromagnetic torque and other electromagnetic parameters under various working conditions including fault-tolerant conditions are determined. At the same time, the thermal circuit method is used to check the hot spot temperature of the generator under various working conditions to explore the fault tolerance necessity and operation reliability of the dual winding permanent magnet wind turbine. Finally, by building a prototype platform, the rationality of the solution model and the accuracy of the calculation results are verified.
RETRACTED: Feature selection using PRACO method for IDS in cloud environment
Authors: Kumar Prashant , Shakti Shivam , Datta Naireet , Sinha Shashwat , Ghosh Partha
Published: July 2022

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
FIFA ranking: Evaluation and path forward
Authors: Szczecinski Leszek , Roatis Iris-Ioana
Published: July 2022

In this work, we study the ranking algorithm used by Fédération Internationale de Football Association (FIFA); we analyze the parameters that it currently uses, show the formal probabilistic model from which it can be derived, and optimize the latter. In particular, analyzing games since the introduction of the algorithm in 2018, we conclude that game’s “importance” (defined by FIFA and used by the algorithm) is counterproductive from the point of view of the predictive capacity of the algorithm. We also postulate that the algorithm should be rooted in the formal modeling principle, where the Davidson model proposed in 1970 seems to be an excellent candidate, preserving the form of the algorithm currently used. The results indicate that the predictive capacity of the algorithm is considerably improved by using the home-field advantage (HFA), as well as the explicit model for the draws in the game. Moderate but notable improvement may be achieved by introducing the weighting of the results with the goal differential, which, although not rooted in a formal modeling principle, is compatible with the current algorithm and can be tuned to the characteristics of the football competition.
Practices of sickle cell disease genetic screening and testing in the prenatal population
Authors: Prince A. , Cruz-Bendezú A. , Gunawansa N. , Wade J. , Coleman-Cowger V. H. , Schulkin J. , Macri C. J.
Published: July 2022

BACKGROUND: Genetic screening and testing are technologies historically underutilized in Black populations despite predicting diseases like sickle cell disease (SCD), which is predominantly found in Blacks. We surveyed prenatal patients to understand choices, beliefs and experiences surrounding genetic screening and testing, specifically for SCD. METHODS: In this cross-sectional study, we surveyed 322 women during prenatal visits. Responses were analyzed to identify barriers to care and education about testing and screening for SCD. Patients rated whether they agreed or disagreed with statements regarding sickle cell health behaviors. We used χ2 tests to compare categorical variables by self-reported race. Binary logistic regression was used to determine the odds ratios and confidence intervals for each outcome. RESULTS: Women were a mean (SD) age of 33.3 (6.1). 42.9% of patients self-identified as White while 41.3% of patients self- identified as Black. Screening questions were adjusted for differences in race, insurance, and education levels to show significant differences in responses between Blacks and Whites for screening for SCD (p = 0.047, OR 95% CI = 0.455 [0.210–0.989]) and plans to meet with genetic counselors (p = 0.049, OR 95% CI = 0.299 [0.090–0.993]). The statements “if sickle cell is not in their family, then it is likely not in themselves or their children,” was significantly different between Black and White populations (p = 0.011, OR 95% CI = 0.207 [0.081–0.526]). CONCLUSION: Our findings suggest gaps in screening, testing, education, and pregnancy management choices between Black and White patients. Research should focus on decreasing these healthcare gaps and improving education that address concerns about SCD for relevant populations.
Mast cell population in the testicle during pathospermia
Authors:   Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation, Kulchenko N.G.
Published: July 2022

Nowadays, male and female infertility factors can cause infertile marriage with the same frequency. It is known that the causes of male infertility can be varicocele, genetic disorders, endocrine diseases, congenital pathologies, injuries and inflammatory diseases. Despite a sufficient set of diagnostic techniques, the form of male infertility remains unidentified (idiopathic) in 1/3 of men. At present, the role of mast cells (MC) in the development of chronic pelvic pain syndrome, chronic prostatitis, and chronic epididymitis are shown. However, the role of MC in the formation of male infertility still remains open. The article presents a clinical case of a male patient with primary infertility and non-obstructive azoospermia, who underwent a testicular biopsy to identify the causes of infertility. Morphological examination of the biopsy specimen revealed the MC population in the testicular interstitium. This particular finding allows to explain the presence of fibrosis in the connective tissue and the epithelium of convoluted seminiferous tubules in this patient. The revealed testicular fibrosis led to a permeability disorder of the blood-testis barrier and a spermatogenic epithelial cell death, resulted in the development of azoospermia in the particular male patient KEYWORDS: male infertility, pathospermia, spermatogenesis disorders, mast cells, fibrosis, azoospermia. FOR CITATION: Kulchenko N.G. Mast cell population in the testicle during pathospermia. Russian Medical Inquiry. 2022;6(4):195–199 (in Russ.). DOI: 10.32364/2587-6821-2022-6-4-195-199.
Una mirada a los péptidos y su potencial aplicación en acuicultura de peces
Authors: Santana Sepúlveda Paula , Guzmán Quimbayo Fanny , Mercado Vianco Luis , Jara Gutiérrez Carlos , Álvarez Álvarez Claudio , Alvarado Almonacid Nancy
Published: July 2022

Mejorar las respuestas fisiológicas de peces es una constante necesidad para incrementar la productividad de piscifactorías. Lo anterior requiere identificar moléculas que puedan ser utilizadas para modular o reforzar su respuesta inmunológica frente a patógenos, regular su sistema endocrino o facilitar su desarrollo reproductivo en cautiverio. En este libro exploramos cómo los péptidos pueden ser utilizados en interesantes estrategias para mejorar el desempeño de peces bajo cultivo, así como también identificar aquellas brechas que aún deben trabajarse para su aplicación a gran escala.
Characterization of Additively Manufactured Circular Disks Using Traditional Computed Tomography Volume Segmentation and Machine Learning Algorithms
Authors:   Sandia National Laboratories, Miers J.C. , Moore D.G. , Branch B.A.
Published: July 2022

Additively manufactured (AM) components contain discontinuities, indications and defects that can change the component’s mechanical performance during high energy impact events. X-ray computed tomography (XCT) reconstructions of AM metastable titanium disks (Ti-5Al-5V-5Mo-3Cr or Ti-5553) were generated on an industrial micro-focus system. Each sample was scanned before and after high velocity impact testing. The porosity resulting from the direct metal laser sintering (DMLS) powder bed fusion machine was detected and characterized. The samples were placed in a gas gun configuration to induce a high-rate tensile load (shock test). The post-test results on the recovered disks contained incipient spall cavities. These features were identified by standard volume segmentation techniques. This inspection data is also evaluated with machine learning (ML) algorithms. A comparison between ML segmentation of the pores/cavities to standard commercial segmentation algorithms will be presented. Improvements using ML were specifically seen in the identification of pores and spall planes in regions of low x-ray attenuation (brightness and contrast). Common XCT artifacts, which include beam hardening and systematic noise, were overcome by the applied ML methods. Porosity and spall plane regions identified by the machine learning analysis were then compared to serial sectioning and scanning electron microscope (SEM) data to judge the precision and accuracy of the machine learning technique. Results show that the CT reconstructed porosity aligned well with the serial sectioned and SEM data. The only discrepancies were in the small pores near the detectability limit and other metrics dependent on the XCT reconstruction resolution.
Subwavelength Microwave Imaging System using a Negative Index Metamaterial Lens
Authors:   Michigan State University, Datta Srijan , Shi Xiaodong , Deng Yiming , Udpa Lalita
Published: July 2022

This paper describes the design of a subwavelength microwave imaging system using a negative index metamaterial (NIM) lens for nondestructive evaluation (NDE) applications. The imaging system consists of a split ring resonator (SRR)-wire based NIM lens, operating at 6.3 GHz, used in conjunction with a homodyne detection system. Simulation studies of the unit cell design are presented followed by experimental verification of left-handed focusing by the NIM lens with a focal spot of size 0.65λ. A subwavelength hole of diameter 0.25λ in a glass fiber reinforced polymer (GFRP) sample is imaged at a stand-off distance of 1.67λ using the proposed system. High SNR and preservation of polarity and phase information associated with synchronous detection provides a NIM lens imaging system that can be used in the field for rapid inspection at large standoff distances.
Zero Group Velocity Modes in Rails: a Numerical Study
Authors:   University of Utah, Wu Yuniing , Zhu Xuan ,   University of Utah, Popovics John ,   University of Illinois, Urbana-Champaign
Published: July 2022

Ultrasonic guided wave propagation along a free rail was simulated to understand the existence of intrinsic zero-group velocity (ZGV) modes. A finite element model was established to spatially sample the complex wave disturbance in the rail to study its dispersion relationships. The sharp resonant phenomenon of ZGV modes was observed in the frequency domain, and multiple ZGV points were identified at finite wavenumbers in the wavenumber-frequency domain. The resonances with positive and negative wavenumbers revealed that the observed ZGV modes result from the interference of two propagating modes traveling in opposite directions. ZGV modes in free rails have the potential for rail defect detection, support condition assessment, and stress-free temperature measurement.
Railroad Crosstie Deflection Measurement via Ultrasonic Airborne Sonar and Computer Vision Techniques
Authors:   University of California San Diego, Hosseinzadeh Ali Zare , Datta Diptojit , di Scalea Francesco Lanza
Published: July 2022

A smart tie-tracking technology is proposed to measure the deflections of railroad crossties by means of non-contact ultrasonic testing in sonar mode and computer vision techniques. The sensing layout consists of an array of air-coupled capacitive transducers (in pulse-echo mode) and a high frame-rate camera, rigidly connected to the main frame of train car. The acquisition system is programmed such that the synchronized waveforms and images are collected and saved as train car moves. In the processing stage, a machine learning-based image classification approach is developed to discriminate tie/ballast images and demarcate the crossties’ boundaries. The relative deflections of the identified crossties are eventually computed by tracking the arrival time of the reflected waves from the surfaces flagged as tie. Further inspection of the deflection profiles can reveal crossties with potential poor ballast support condition. The proposed ‘tie sonar’ system was prototyped and used to reconstruct the deflection profile of the crossties scanned during a series of test runs at the Rail Defect Testing Facility of UC San Diego as well as the BNSF yard in San Diego, CA.
High-Resolution Millimeter-Wave Near-Field Evaluation of Additive Manufactured (AM) Polymeric Structures
Authors:   Iowa State University of Science and Technology, Ahmadi Farzaneh , Al Qaseer Mohammad Tayeb , Zoughi Reza
Published: July 2022

Additive manufacturing (AM) is a rapidly growing industry whose utility has been expanded beyond metals and to other materials such as polymers, ceramics, and concrete, to name a few. However, advancement in the development of inspection techniques, particularly in-line nondestructive testing (NDT) methods, lags significantly. Most of the research in developing such methods has focused on metal-based AM. This paper presents a high-resolution dielectric-loaded waveguide probe for detecting small flaws in 3D printed polymeric structures. The electromagnetic (EM) design and optimization of such a probe are discussed in this paper. The probe design is based on concentrating the interrogating electric field of an open-ended waveguide in a thin dielectric slab insert. This results in obtaining a higher spatial resolution than when using only the open-ended waveguide. Subsequently, such a probe was fabricated at a frequency of 74 GHz (V-band (50-75 GHz)) and was used to raster scan a Thermoplastic Polyurethane (TPU) sample, with very small surface flaws, to generate a near-field image. The resulting image confirms the usefulness of this technique as a potentially viable method for in-line monitoring of polymeric AM structures.
NDE Data Fusion between Inconsistent Geometries
Authors:   Iowa State University, Liu Lijie , Shen Weijun , Krishnamurthy Adarsh , Holland Stephen D. , Zhang Zhan
Published: July 2022

Data fusion in the NDE digital thread and digital twin requires spatial registration, but in many cases, as-designed and as-built geometries are different. Because of the additional prior knowledge of geometry and topology, a 3D CAD modeling context shows great potential to seamlessly integrate different kinds of NDE data in the digital thread. Non-Uniform Rational B-splines (NURBS) are the standard representation of surfaces in a CAD system. Recently, a differentiable NURBS framework was developed with mathematical formulations of the NURBS derivatives with respect to the input parameters. Using this framework, we perform gradient-based optimization. However, it is still challenging to transform the NDE data to a usable reference CAD geometry with a consistent as-built CAD model and a measured point cloud to support data fusion applications. We have tested this approach on a bar geometry as proof of concept. Our preliminary results show that the approach can fit the distorted surfaces to the measured NDE data well without introducing gaps between the surfaces of the CAD model.
A Machine Learning Framework for Rail Neutral Temperature Estimation using Impulse Vibrational Responses
Authors:   University of Utah, Wu Yuning , Huang Chi-Luen ,   University of Illinois, Urbana-Champaign, Lee Sangmin ,   University of Illinois, Urbana-Champaign, Zhang Keping ,   University of Utah, Zhu Xuan ,   University of Utah, Popovics John ,   University of Illinois, Urbana-Champaign, Dersch Marcus ,   University of Illinois, Urbana-Champaign
Published: July 2022

Longitudinal rail force management of continuous welded rail (CWR) is important for safe and efficient railroad operation. A key parameter to measure and monitor is the rail neutral temperature (RNT) or the stress-free temperature. The team proposed a supervised learning framework to estimate the RNT using impulse vibrational responses from CWRs. We first established an instrumented field site on a revenue-service line and collected impulse vibrational response data covering a wide range of temperature and thermal stress. Then, we trained a data-driven model that uses rail temperatures and modal frequencies as the input for in-situ RNT prediction. The results demonstrated that the proposed framework could provide RNT estimation with a reasonable precision (±5 ºF)
Total Focusing Method with Laser-Generated Ultrasonic Waves for Defect Detection in Finite Plates
Authors:   General Motors LLC, McGovern Megan E. , Bruder Dmitriy D. , James Robin , Gattani Vineet
Published: July 2022

Total Focusing Method (TFM) was employed using laser-generated ultrasonic plate waves. The goal was to assess the feasibility of using this technique for applications where testing constraints necessitate couplant-free, remote, guided-wave conditions. The application under consideration is using laser-generated TFM to assess ultrasonically welded battery tab-to-electrode foil stack joints. It was determined that laser-generated guided wave TFM can be used to remotely assess defects in a finite plate when the defects are strong reflectors in the plane of propagation. The finite dimensions of the tab necessitate a strong understanding of the edge reflection effects on the TFM image. The guided wave modes used in this study were strongly affected by scattering due to a complicated weld surface. Future work will investigate methods to compensate for the strong scattering, the use of other guided wave geometries, out of plane TFM reconstruction for other weld defect types, as well as apodization effects.
Uncertainty quantification in immersion ultrasound measurements using a Bayesian inferencing approach
Authors:   Lawrence Livermore National Laboratory, Mukherjee Saptarshi , Fairbanks Hillary , Lum Jordan , Stobbe David S. , Karimi Seeman , Tringe Joseph W.
Published: July 2022

Ultrasound nondestructive evaluation (NDE) methods often use a deterministic inverse model to reconstruct material properties. Such techniques rely on accurate information about the material such as wave-speed and attenuation at different frequencies, as well as information about the measurement system such as transducer radiation properties and measurement noise. However, in reality there is uncertainty associated with each of these important quantities. This is particularly important for structures manufactured using advanced manufacturing techniques since the mechanical properties of materials in these structures can vary significantly across the manufactured object. Prior work in uncertainty quantification for ultrasound NDE has been mostly limited to either simulation datasets for guided wave or resonant ultrasound measurements in metals prepared using conventional subtractive manufacturing techniques. Here we describe a new process for quantifying and incorporating the uncertainty in metal additive manufacturing from immersion ultrasound measurements and demonstrate that this can better defect detection with higher accuracy and confidence.
Melt Pool Temperature Prediction Based on Recurrent Neural Network for Directed Energy Deposition
Authors:   Iowa State University, Liu Lijie , Shen Weijun , Jiang Yiqun , Jiang Xuepeng , Zhang Zhan , Qin Hantang , Li Qing
Published: July 2022

In directed energy deposition, the melt pool temperature is closely related to the microstructures and defects, thus significantly affecting the final part quality. Multiple factors such as laser power, scanning speed, spot size, and powder feed rate can affect the melt pool temperature profiles. It is critical to determine the melt pool temperature distribution and history during the material deposition. However, the high-energy beam and metal material interaction in the molten pool is a complex coupled process with physical metallurgy changes, which makes it challenging to use the experimental methods to investigate the melt pool temperature distribution under different processing parameters. To address this challenge, we establish two data-driven models using machine learning based on extreme gradient boosting (XGBoost) and long short-term memory (LSTM) correspondingly to predict the melt pool temperature in a thin-wall structure deposition. The experimental results have shown that the prediction of LSTM is sufficiently accurate and fast for in-situ correction. The proposed predictive models are expected to facilitate DED process optimization in melt pool thermal-related properties.
In-Situ Optical Tomography for Selective Laser Melting
Authors:   Southern Illinois University Carbondale, Seavers Connor , Chu Tsuchin
Published: July 2022

Selective laser melting (SLM) has become one of the most common metal additive manufacturing (AM) processes in industries such as medical and aerospace due to its ability to produce highly specialized end-use parts of great complexity. However, current SLM products are prone to process-induced defects, most importantly porosity, which can greatly alter the strength of the part. Therefore, in this study, in-situ monitoring is investigated as a method for detecting the formation of defects during the SLM process. Layerwise optical tomography (OT) images are collected during SLM fabrication of six test samples with planned defects, and subsequently undergo image processing and analysis for identification of anomalous signatures during the build process. The image processing framework employs an average squared difference (ASD) metric to elucidate defects within the image, then feeds the output into an automated k-means clustering algorithm for segmentation and classification. While the k-means classification approach ultimately proved to be sensitive to noise in the images, the image processing workflow was still able to isolate defects, often providing a clear segmentation of the defect in the final output.
Nondestructive Detection of In-Plane Wrinkles in Carbon Fiber Laminates Using Eddy Current and Ultrasonic Testing
Authors:   Baylor University, Newton Matthew , Chowdhury Tonoy ,   Baylor University, Gravagne Ian , Jack David
Published: July 2022

Nondestructive detection of the in-plane wrinkles (sometimes termed marcelling in various industrial settings) of unidirectional carbon fiber reinforced plastic (CFRP) laminates is of interest in a wide variety of industries as the in-plane wrinkles significantly reduce the mechanical performance of the manufactured composite structure. In this work, a comparative study is presented to detect in-plane wrinkles on a 5 ply unidirectional CFRP laminate with a customized eddy current testing (ECT) and ultrasonic testing (UT) system. A manufacturing method to inducing controlled marcelling within a specified lamina is introduced, and fabricated components are then inspected using both ECT and UT. Data suggests that the results from the directionally biased ECT system effectively captures both the presence of an in-plane wrinkle and quantify the shape of the wrinkle, whereas the results from the ultrasonic inspection were not able to properly quantify the wrinkle extent. Using the anisotropic conductive property of CFRP, the eddy current system was able to clearly detect spatial variations in the local fiber orientation, waviness steepness angle, and waviness amplitude, three different parameters used to quantify the wrinkle impact on the structural performance.
Моделювання логістичного процесу евакуації промислового підприємства у воєнний час
Authors: Fedorovich Oleg , Pronchakov Yurii , Rybka Kseniia , Leshchenko Yuliia
Published: July 2022

The complex problem of a multicriteria nature that is related to the justification of the new location for the evacuated enterprise is stated and solved. The simulation of the logistic process of evacuation in the conditions of threats and vulnerabilities of wartime is carried out. The relevance of the study is related to the justification of the possible location of the industrial enterprise production, considering the process of technological equipment transportation to the rear in a heterogeneous transport network. Also, the processes of moving the evacuated industrial enterprise to a new location and establishing the production in the new place are studied. The study simulates the logistical process of industrial enterprise evacuation in terms of wartime threats and vulnerabilities. A method to justify the location of the evacuated industrial enterprise that is based on a multivariate analysis with the use of qualitative expert assessments in the form of linguistic variables values is proposed. The complex dynamics of military cargo and technological equipment delivery to the new location are considered. This is done by means of simulation modeling that considers the specifics of a heterogeneous transport network and the risks and threats of wartime. An agent-based simulation model of the logistical process of the industrial enterprise evacuation has been developed. A new algorithm to minimize the delivery time of cargo and technological equipment that considers possible risks and threats and makes it possible to find the optimal route in a heterogeneous transport network is presented. An optimization model to locate the technological equipment of the evacuated industrial enterprise in the new territory, considering the criteria of time, cost and risks has been created. The multi-criteria optimization of the technological equipment location was carried out under the conditions of conflicting criteria, considering the requirements of wartime. The scientific novelty of the study is related to the development of methods and models of the industrial enterprise evacuation process based on agent-based simulation modeling, integer (Boolean) optimization, expert evaluation, use of linguistic variables that ultimately makes possible to justify the logistics of industrial enterprise evacuation in wartime. The results of the study should be used to plan the evacuation process of the industrial enterprise considering the requirements of wartime.
ОРГАНІЗАЦІЙНО-ПРАВОВЕ ЗАБЕЗПЕЧЕННЯ ФУНКЦІОНУВАННЯ СИСТЕМИ УПРАВЛІННЯ У СФЕРІ БЕЗПЕКИ ТА ОХОРОНИ ДЕРЖАВНОГО КОРДОНУ
Authors: Slobodyan I.
Published: July 2022

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СТРАТЕГІЧНЕ ПЛАНУВАННЯ РОЗВИТКУ ТЕРИТОРІАЛЬНО-ВИРОБНИЧИХ СИСТЕМ ПРОФЕСІЙНО-ТЕХНІЧНОЇ ОСВІТИ ЯК ІННОВАЦІЙНИЙ МЕХАНІЗМ УПРАВЛІННЯ АГРАРНОГО СЕКТОРА УКРАЇНИ
Authors: Kravchenko L.
Published: July 2022

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НАЦІОНАЛЬНІ СТИЛІ ЛІДЕРСТВА
Authors: Melnyk N. , Mysak H.
Published: July 2022

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СТАЛИЙ РОЗВИТОК СФЕРИ ВОДОПОСТАЧАННЯ ТА ВОДОВІДВЕДЕННЯ В УКРАЇНІ: ПРОБЛЕМИ ТА ПЕРСПЕКТИВИ
Authors: Oliinyk N.
Published: July 2022

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Erciyes Üniversitesi Hayvan Hastanesi’ne 2019-2021 Yılları Arasında Getirilen Neonatal İshalli Bu-zağılarda Majör Enteropatojenlerin Yaygınlığının Araştırılması
Authors: EKİNCİ Gencay , TÜFEKÇİ Emre , ONMAZ Ali Cesur , ÇİTİL Mehmet , KELEŞ İhsan , GÜNEŞ Vehbi
Published: July 2022

Bu çalışma, Kayseri ve civar illerindeki çiftliklerden 01 Ağustos 2019 ve 31 Ağustos 2021 tarihleri arasında, Erciyes Üniversitesi, Veteriner Fakültesi, Eğitim Araştırma ve Uygulama Hastanesi’ne getirilen neonatal ishalli buzağılarda BRV, BCoV, E. coli K99+, Cryptosporidium spp. ve Giardia spp.’nin görülme oranlarını belirlemeyi amaçlayan retros-pektif bir araştırmadır. Belirtilen periyotlar arasında, hastaneye toplamda 1839 buzağı getirildiği tespit edildi. Bu buzağı-lardan 863’ünün İç Hastalıkları Anabilim Dalı Ruminant Kliniğine getirildiği ve bunlardan 560’ının (%65) klinik ishal belir-tisine sahip olduğu belirlendi. İshalli buzağılardan alınan dışkı örneklerinden, tek bir enteropatojen olarak en çok, BCoV (%21.7), sonra sırasıyla; Cryptosporidium spp. (%18.3), ETEC K99+ (F5) (%14.3), BRV (%11.4), Giardia spp. (%0.6) tespit edildiği belirlendi. Birden fazla enteropatojen olarak ise en çok, Cryptosporidium spp. + BRV (8.0%), sonra sıra-sıyla; BRV + BCoV (%7.4), Cryptosporidium spp. + BCoV (%6.3), BRV + ETEC K99+ (%1.1), BRV + BCoV + Cryptos-poridium spp. (%2.3) teşhisi konulduğu gözlendi. 1-7 günlük neonatal ishalli buzağılarda en çok ETEC K99+ (%34.7), 8-14 günlük neonatal ishalli buzağılarda ise en çok Cryptosporidium spp. (%23.9) kaynaklı ishal vakalarının görüldüğü belirlendi. İlkbahar ve kış mevsiminde, en çok BCoV (sırasıyla, %22.5, %25.5), yaz ve sonbahar mevsiminde ise en çok Cryptosporidium spp. (sırasıyla, %26.9, %31.8) kaynaklı ishal teşhisi konulduğu görüldü. Sonuç olarak, 2019-2021 yılları arasında, Kayseri ve civar illerinden Erciyes Üniversitesi, Veteriner Fakültesi, Eğitim Araştırma ve Uygulama Hastanesi’ne getirilen neonatal ishalli buzağılarda, en çok BCoV kaynaklı buzağı ishallerinin görüldüğü ortaya konuldu. Enteropatojenlerin prevalansının örnekleme yeri, zamanı, mevsim gibi çeşitli faktörlere bağlı olarak değişebileceği ve bu çalışmadan elde edilen bulguların buzağı ishalinin önlenmesi için gerekli profilaktik ve yönetimsel önlemlerin alınma-sında faydalı olabileceği sonucuna varıldı.
Der Grund für den Staat
Authors: Pedroso Nilda Da Conceição
Published: July 2022

Mit dieser Arbeit wollen wir die Ordner der historischen Sammlung des Nationalarchivs untersuchen. Sie enthalten die Captainular Acts der Versammlungen der Nationalen Himmelfahrt Lobby in den Jahren 1805 und 1806. Unsere Absicht ist es, durch diese Forderungen zu demonstrieren und eine heimtückische und kolonisierte Himmelfahrt zu entlarven, aber fleißig, politisiert und sich entwickelnd. Zeigen Sie das gleiche, die Tätigkeit eines Staatsapparates, der in der Vergangenheit zusammen mit den Menschen eine wichtige Rolle gespielt hat: der Cabildo. Auf der anderen Seite wollen wir dazu beitragen, Fragen der Jahrhunderte zu klären, die mit diesem monographischen Werk der Vergangenheit angehören und in die historische Gegenwart gebracht werden.
Síntesis de un complejo de glicinato de cobre (II) monohidrato
Authors: Oliveira Leandro José Dias Gonçalves de
Published: July 2022

Los compuestos de coordinación se caracterizan básicamente por un ion de un metal de bloque D, llamado ácido Lewis rodeado de ligantes llamados bases Lewis, y por lo general sus sales tienen una coloración intensa cuando están en solución. El glicinato de cobre (II) monohidrato es un sólido de color azul-verde, y tiene formas isoéricas cis/trans. El presente trabajo tiene como objetivo informar el proceso de síntesis y caracterización a nivel cualitativo de este complejo en el laboratorio químico del Colegio Municipal Governador Israel Pinheiro, João Monlevade, MG. Los resultados del experimento revelaron cristales de color característicos del compuesto previsto y rendimiento porcentual favorable.