bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding
Authors: Zhou Baifan , Pychynski Tim , Reischl Markus , Kharlamov Evgeny , Mikut Ralf 
Published: March 2022

AbstractDigitalisation trends of Industry 4.0 and Internet of Things led to an unprecedented growth of manufacturing data. This opens new horizons for data-driven methods, such as Machine Learning (ML), in monitoring of manufacturing processes. In this work, we propose ML pipelines for quality monitoring in Resistance Spot Welding. Previous approaches mostly focused on estimating quality of welding based on data collected from laboratory or experimental settings. Then, they mostly treated welding operations as independent events while welding is a continuous process with a systematic dynamics and production cycles caused by maintenance. Besides, model interpretation based on engineering know-how, which is an important and common practice in manufacturing industry, has mostly been ignored. In this work, we address these three issues by developing a novel feature-engineering based ML approach. Our method was developed on top of real production data. It allows to analyse sequences of welding instances collected from running manufacturing lines. By capturing dependencies across sequences of welding instances, our method allows to predict quality of upcoming welding operations before they happen. Furthermore, in our work we strive to combine the view of engineering and data science by discussing characteristics of welding data that have been little discussed in the literature, by designing sophisticated feature engineering strategies with support of domain knowledge, and by interpreting the results of ML analysis intensively to provide insights for engineering. We developed 12 ML pipelines in two dimensions: settings of feature engineering and ML methods, where we considered 4 feature settings and 3 ML methods (linear regression, multi-layer perception and support vector regression). We extensively evaluated our ML pipelines on data from two running industrial production lines of 27 welding machines with promising results.
Topological Imaging Methods for the Iterative Detection of Multiple Impedance Obstacles
Authors: Louër F. Le , Rapún M.-L. 
Published: March 2022

AbstractIn this paper, we investigate shape inversion algorithms based on the computation of iterated topological derivatives for the detection of multiple particles coated by a complex surface impedance in two- and three-dimensional acoustic media. New closed-form formulae for the topological derivative of the misfit functional are derived when an approximate set of unknown particles has already been recovered. Proofs rely on the computation of shape derivatives followed by the topological asymptotic analysis of a boundary integral equation formulation of the forward and adjoint problems. The relevance of the theoretical results is illustrated by various 2D and 3D experiments using monochromatic imaging algorithms either fully or partially based on topological derivatives.
Relation between chemical composition, morphology, and microstructure of poly(ether ether ketone)/reduced graphene oxide nanocomposite coatings obtained by electrophoretic deposition
Authors: González-Castillo Eduin I. , Žitňan Michal , Torres Yadir , Shuttleworth Peter S. , Galusek Dušan , Ellis Gary , Boccaccini Aldo R. 
Published: March 2022

AbstractThe effect of the chemical composition on the morphology and microstructure of poly(ether ether ketone) (PEEK)/reduced graphene oxide (RGO) nanocomposite coatings is analyzed. RGO induced three main morphological features in the nanocomposites: (i) a large-scale co-continuous morphology related to nanosheets whose basal planes were mainly aligned with the coating surface, (ii) a dendritic morphology of PEEK domains, and (iii) irregular domains related to the deposition of PEEK particles wrapped by the nanosheets. The development of these morphological features was influenced by the RGO content, allowing the modification of the surface roughness. RGO also induced changes in the melting and non-isothermal crystallization of the polymeric matrix and promoted transcrystallinity in PEEK that, in turn, was a key factor in the development of the final microstructure. In addition, polymer chain mobility was observed to be hindered at high nanofiller concentrations, increasing the glass transition temperature, and diminishing the recrystallization of the polymeric matrix.
Choice Matters More with Others: Choosing to be with Other People is More Consequential to Well-Being than Choosing to be Alone
Authors: Uziel Liad , Schmidt-Barad Tomer 
Published: March 2022

AbstractStable social relationships are conducive to well-being. However, similar effects are not reported consistently for daily social interactions in affecting episodic (experiential) subjective well-being (ESWB). The present investigation suggests that the choice of being in a social context plays an important moderating role, such that social interactions increase ESWB only if taken place by one's choice. Moreover, it is argued that choice matters more in a social context than in an alone context because experiences with others are amplified. These ideas were tested and supported in two studies: An experiment that manipulated social context and choice status, and a 10-day experience-sampling study, which explored these variables in real-life settings. Results showed that being with others by one’s choice had the strongest positive association with ESWB, sense of meaning, and control, whereas being with others not by one’s choice—the strongest negative association with ESWB. Effects of being alone on ESWB also varied by choice status, but to a lesser extent. The findings offer theoretical and practical insights into the effects of the social environment on well-being.
The tragic complexity of Purgatory
Authors: Tassoni Luigi 
Published: March 2022

AbstractThe text is part of a broader study on the perception of tragic perspective compared with our contemporary tragic sense. In addition to have a particular narratological relevance, the persistence of tragic level in the second cantica of the Comedy produces a decisive effect in Dante’s discourse, and proposes a different meaning of Allegory. One of the results of this investigation concerns the dramatic language, which is determined where Dante’s allegorical representation takes place, whereas the Allegory itself is forbidden by the variables of the tragic discourse, and is impossible to realize. However, the tragic perspective of the second Cantica is not constant, as in Hell, and it has its specific climax, marked by the acceleration of the time, the space of waiting, the crisis of salvific destiny, wich, in the arc od Dante’s narration, bind the characters to doubt and to need to overcome the tragic and irresolvable condition of being without destiny.
Mechanistic Insights into Ameliorating Effect of Geraniol on d-Galactose Induced Memory Impairment in Rats
Authors: Atef Marwa Mohamed , Emam Marwa Nagy , Abo El Gheit Rehab E. , Elbeltagi Eman M. , Alshenawy H. A. , Radwan Doaa A. , Younis Reham L. , Abd-Ellatif Rania Nagi 
Published: March 2022

AbstractGeraniol (GE), an important ingredient in several essential oils, displayed pleiotropic biological activities through targeting multiple signaling cascades. In the current study, we aimed to examine the protective effect of GE on d-galactose (d-gal) induced cognitive impairment and explore the underlying mechanisms. Forty male Wistar rats (8 weeks old) were randomly categorized into 4 groups; Group I (saline + vehicle [edible oil]), group II (saline + geraniol) (100 mg/kg/day orally), group III (d-galactose) (100 mg/kg/day subcutaneously injected), and group IV (d-galactose + geraniol). Behavioral impairments were evaluated. Brain levels of malondialdehyde (MDA) and reduced glutathione (GSH) as well as superoxide dismutase (SOD) and acetylcholinesterase (AchE) activities were estimated. The levels of inflammatory markers [tumor necrosis factor-alpha (TNF-α), interleukin (IL)-1β, IL-6, and nuclear factor kappa beta (NF-kβ)], endoplasmic reticulum stress sensors [inositol requiring protein 1(IRE1) and protein kinase RNA–like endoplasmic reticulum kinase (PERK)], brain-derived neurotrophic factor (BDNF), and mitogen-activated protein kinases (MAPK) pathway were measured by ELISA. Also, hippocampal histopathological assessment and immunohistochemical analysis of glial fibrillary acidic protein (GFAP) and caspase-3 were performed. Glucose regulated protein 78 (GRP78) and C/EBP homologous protein (CHOP) mRNA expression and protein levels were assessed. GE effectively ameliorated aging-related memory impairment through increasing GSH, BDNF, Ach levels, and SOD activity. Additionally, GE treatment caused a decrease in the levels of MDA, inflammatory mediators, and ER stress sensors as well as the AchE activity together with concomitant down-regulation of GRP78 and CHOP mRNA expression. Moreover, GE improved neuronal architecture and rat's spatial memory; this is evidenced by the shortened escape latency and increased platform crossing number. Therefore, GE offers a unique pharmacological approach for aging-associated neurodegenerative disorders.
Graphical Abstract
Valorisation of algal biomass to value-added metabolites: emerging trends and opportunities
Authors: Uma V. S. , Usmani Zeba , Sharma Minaxi , Diwan Deepti , Sharma Monika , Guo Miao , Tuohy Maria G. , Makatsoris Charalampos , Zhao Xiaobin , Thakur Vijay Kumar , Gupta Vijai Kumar 
Published: March 2022

AbstractAlgal biomass is a promising feedstock for sustainable production of a range of value-added compounds and products including food, feed, fuel. To further augment the commercial value of algal metabolites, efficient valorization methods and biorefining channels are essential. Algal extracts are ideal sources of biotechnologically viable compounds loaded with anti-microbial, anti-oxidative, anti-inflammatory, anti-cancerous and several therapeutic and restorative properties. Emerging technologies in biomass valorisation tend to reduce the significant cost burden in large scale operations precisely associated with the pre-treatment, downstream processing and waste management processes. In order to enhance the economic feasibility of algal products in the global market, comprehensive extraction of multi-algal product biorefinery is envisaged as an assuring strategy. Algal biorefinery has inspired the technologists with novel prospectives especially in waste recovery, carbon concentration/sequestration and complete utilisation of the value-added products in a sustainable closed-loop methodology. This review critically examines the latest trends in the algal biomass valorisation and the expansive feedstock potentials in a biorefinery perspective. The recent scope dynamics of algal biomass utilisation such as bio-surfactants, oleochemicals, bio-stimulants and carbon mitigation have also been discussed. The existing challenges in algal biomass valorisation, current knowledge gaps and bottlenecks towards commercialisation of algal technologies are discussed. This review is a comprehensive presentation of the road map of algal biomass valorisation techniques towards biorefinery technology. The global market view of the algal products, future research directions and emerging opportunities are reviewed.
Economic potential of site-specific pesticide application scenarios with direct injection and automatic application assistant in northern Germany
Authors: Rajmis Sandra , Karpinski Isabella , Pohl Jan-Philip , Herrmann Marco , Kehlenbeck Hella 
Published: March 2022

AbstractA growing and promising sector of precision agriculture is the site-specific application of pesticides, having a high potential for reductions in pesticide use. Within the research project ‘AssSys’, site-specific pesticide applications with a direct injection sprayer system and an automatic application assistant were evaluated economically with respect to herbicide and fungicide applications. The application assistant aims to support farmers in decision-making and implementation of site-specific pesticide applications either in the planning stage or as ex-post analysis. The economic assessment was based on field trials and scenario analysis referring to a model farm. The field trials were conducted in 2018 and 2019 in northern Germany. In the scenario analysis, two site-specific application scenarios were compared to conventional uniform treatment (100% of the field area). Weed monitoring was conducted as (1) standard procedure according to integrated pest management, (2) camera-based and (3) drone-based in the field trials. The pesticide application costs include pesticide costs, labour and machine costs of monitoring and pesticide applications. Investment costs of the necessary technical equipment for site-specific applications were included as annual labour and machine costs. As a major key performance indicator of partial budgeting at field level, extended gross margins were calculated. The economic scenario analysis showed pesticide application cost savings from 26 to 66% for site-specific applications compared to conventional applications. The average extended gross margin for site-specific applications of 787 € ha−1compared to 631 € ha−1for conventional application showed a clear economic advantage of the site-specific application scenarios. Site-specific pesticide applications can support farmers in implementing precise, sustainable and economically beneficial pesticide management. The technology presented may contribute to meet the goals of the European Green Deal to reduce use and risks of pesticides.
Teaching About Electricity in Primary School Multimodality and Variation Theory as Analytical Lenses
Authors: Preston Christine M. , Hubber Peter J. , Xu Lihua 
Published: March 2022

AbstractPrimary school topics involving abstract concepts are challenging to teach. Electric circuits can be simply constructed but complex to explain. New approaches in teaching students for understanding are needed to advance practice in primary science. This paper combines the strengths of multimodality research perspectives with variation theory to provide insights into a teaching sequence designed for year 6 students. Application of a representation construction approach (RCA) provides opportunities for multimodal meaning-making of electric circuits. The case study adopted a design-based research method to investigate teaching electric circuits. Data collection involved video capture of classroom practice, teacher and student interviews, student journal entries and assessment artefacts, field notes, and pre-test and post-test results. Design principles included identifying key ideas, devising a lesson sequence emphasising energy transfer and transformation, hands-on exploration using multimodal representations in response to learning challenges, and student journaling. Students’ metarepresentational competence was also developed through evaluation, negotiation, and creation of representations and models of electric circuits. Representational challenges followed by strategic teacher-led discussion facilitated students’ developing understanding through focusing attention on critical features. Deep learning was evidenced by journal records, formative and summative assessment artefacts, and post-test responses. RCA principles were instrumental in the successful design of an effective teaching sequence through focus on critical aspects of energy. We advocate a RCA for the design of a multimodal learning sequence. Variation theory was a useful analytical framework to understand the enactment of the design sequence. The study contributes to the challenge of rethinking traditional teaching practices in primary science.
Physiologic Lesion Assessment to Optimize Multivessel Disease
Authors: Bharmal Murtaza , Kern Morton J. , Kumar Gautam , Seto Arnold H. 
Published: March 2022

Abstract
Purpose of Review
Multivessel coronary artery disease, defined as significant stenosis in two or more major coronary arteries, is associated with high morbidity and mortality. The diagnosis and treatment of multivessel disease have evolved in the PCI era from solely a visual estimation of ischemic risk to a functional evaluation during angiography. This review summarizes the evidence and discusses the commonly used methods of multivessel coronary artery stenosis physiologic assessment.

Recent Findings
While FFR remains the gold standard in coronary physiologic assessment, several pressure-wire-based non-hyperemic indices of functional stenosis have been developed and validated as well as wire-free angiographically derived quantitative flow ratio. Identifying and treating functionally significant coronary atherosclerotic lesions reduce symptoms and major adverse cardiovascular events.

Summary
Coronary physiologic assessment in multivessel disease minimizes the observer bias in visual estimates of stenosis, changes clinical management, and improves patient outcomes.
Visual Snow: Updates on Pathology
Authors: Fraser Clare L. 
Published: March 2022

Abstract
Purpose of Review
Until the last 5 years, there was very little in the literature about the phenomenon now known as visual snow syndrome. This review will examine the current thinking on the pathology of visual snow and how that thinking has evolved.

Recent Findings
While migraine is a common comorbidity to visual snow syndrome, evidence points to these conditions being distinct clinical entities, with some overlapping pathophysiological processes. There is increasing structural and functional evidence that visual snow syndrome is due to a widespread cortical dysfunction. Cortical hyperexcitability coupled with changes in thalamocortical pathways and higher-level salience network controls have all shown differences in patients with visual snow syndrome compared to controls.

Summary
Further work is needed to clarify the exact mechanisms of visual snow syndrome. Until that time, treatment options will remain limited. Clinicians having a clearer understanding of the basis for visual snow syndrome can appropriately discuss the diagnosis with their patients and steer them towards appropriate management options.
Chitosan-Encapsulated Nano-selenium Targeting TCF7L2, PPARγ, and CAPN10 Genes in Diabetic Rats
Authors: Abozaid Omayma A. R. , El-Sonbaty Sawsan M. , Hamam Neama M. A. , Farrag Moustafa A. , Kodous Ahmad S. 
Published: March 2022

AbstractThis study investigates the antidiabetic and antioxidant potential of chitosan-encapsulated selenium nanoparticles in streptozotocin-induced diabetic model. Glibenclamide was used as a reference antidiabetic drug. Forty-eight adult male Wistar rats were used along the study and divided equally into 6 groups of (I) normal control, (II) chitosan-encapsulated selenium nanoparticles (CTS-SeNPs), (III) glibenclamide, (IV) streptozotocin (STZ), (V) STZ + CTS-SeNPs, and (VI) STZ + Glib. The animals were sacrificed on the 35th day of the experiment. Serum glucose, insulin, IGF-1, ALT, AST, CK-MB, oxidative stress, lipid profile, and inflammatory parameters were subsequently assessed. Also, the expression level of TCF7L2, CAPN10, and PPAR-γ genes were evaluated using qPCR. In addition, histopathological studies on pancreatic tissue were carried out. The results revealed that STZ induced both diabetes and oxidative stress in normal rats, manifested by the significant changes in the studied parameters and in the physical structure of pancreatic tissue. Oral administration of CTS-SeNPs or Glib results in a significant amelioration of the levels of serum fasting blood glucose, insulin, IGF-1, AST, ATL, and CK-MB as compared with STZ-induced diabetic rats. CTS-SeNPs and Glib diminished the level of lipid peroxidation, increased total antioxidant capacity level, as well as possessed strong inhibition against serum α-amylase and α-glucosidase activities. Diabetic animals received CTS-SeNPs, or Glib demonstrated a significant (p < 0.05) decrease in the expression level of TCF7L2 and CAPN10 genes with a significant increase in the expression level of PPAR-γ gene, compared to STZ group. The above findings clarify the promising antidiabetic and antioxidant effect of CTS-SeNPs, recommending its inclusion in the currently used protocols for the treatment of diabetes and in the prevention of its related complications.
Graphical abstract
Examining the relationships between emotional disorder symptoms in a mixed sample of community adults and patients: A network analysis perspective
Authors: De la Rosa-Cáceres A. , Sayans-Jiménez P. , Stasik-O’Brien S. , Sanchez-Garcia M. , Fernández-Calderón F. , Díaz-Batanero Carmen 
Published: March 2022

Abstract
According to the literature, comorbidity rates observed on emotional disorders are linked to how the main diagnostic classification systems have traditionally defined these disorders. This paper aims to analyze the structure of symptoms evaluated with the Inventory of Depression and Anxiety Symptoms-II (IDAS-II) with network analysis. A mixed sample (n = 2021) of 1692 community adults and 329 patients was used. 14.79% (n = 299) of the sample met the diagnostic criteria for at least one DSM-5 mental disorder and 5.29% (n = 107) had diagnostic comorbidity. The sample was randomly divided into two sub-samples: estimation sample (n = 1010) and replication sample (n  = 1011). The detection of community structures was carried out on estimation sample using the walktrap algorithm. Four local inference measures were estimated: Strength, one-step Expected Influence, two-step Expected Influence, and node predictability. Exploratory graphic analysis of modularity yielded an optimal solution of two communities on estimation sample: first linked to symptoms of depression and anxiety and second grouping symptoms of bipolar disorder and obsessive – compulsive disorder. Mania, Panic, Claustrophobia, and Low Well-Being Bridge emerged as bridge symptoms, connecting the two substructures. Networks estimated on replication subsamples did not differ significantly in structure. Dysphoria, Traumatic Intrusions and Checking and Ordering were the symptoms with greatest number of connections with rest of the network. Results sheds light on specific links between emotional disorder symptoms and provides useful information for the development of transdiagnostic interventions by identifying the influential symptoms within the internalizing spectrum.
The Shadow that Hovered Over: Gender Salience in Eating Disorder Recovery
Authors: Strobel Connor B. S. 
Published: March 2022

AbstractStudies examining the social forces behind eating disorders have found that unrealistic conceptions of feminine beauty exert pressure on millions of women suffering from eating disorders. However, untenable feminine ideals do not explain the social factors affecting men. Utilizing narrative and content analyses of accounts of women and men on Tumblr and eating disorder recovery support groups, this paper finds that men experience eating disorders and recover differently from women. Gender salience, and not simply femininity, had a powerful effect on the recovery process for both women and men. Drawing from the sociologies of narrative, gender, and masculinity studies, this study provides a more nuanced and consequential way of understanding eating disorder recovery and how recovery trajectories vary by gender. Four categorical narrative types emerged from the sample: Ecological, Sickened, Abused, and Warrior. Language in the narratives relied on traditional gender roles, and each narrative lead to different proportions of recovery outcomes. Individuals in this study used one of four narrative types. The warrior narrative, which was the only one used by men, was associated with a higher rate of relapse. The propensity to relapse varied between the narrative types, suggesting some may be more conducive for recovery.