Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameter and state estimation of nonlinear systems with applications in neuroscience

The focus of this work is deterministic parameter and state estimation of nonlinear systems with applications to neuroscience. Estimation in neuroscience typically involves the reconstruction of unmeasured neural activity from measurements of the human brain. We envisage that estimation plays a crucial role in neuroscience because of the possibility of creating new avenues for neuroscientific studies and for the development of diagnostic, management and treatment tools for diseases such as Epilepsy and Parkinsons disease. One of the most used measurements is the electroencephalogram (EEG). To this end, we consider lumped-parameter nonlinear models with EEG as the output, known as neural mass models. Four observers are proposed in this thesis: (1) a nonlinear observer, (2) robust circle criterion observers, (3) an adaptive observer and (4) the supervisory observer. These observers are synthesised for classes of nonlinear systems, that cover some of the commonly used neural mass models. Two state observers are shown and designed respectively, in Part I, to be robust towards input and measurement noise, as well as small perturbations in parameters. In the absence of noise and perturbations, the estimates converge exponentially to the true values. The convergence of estimates to their true values is with some error in the presence of noise and perturbations. Chapter 3 presents a nonlinear observer specific to the class of neural mass models considered. In Chapter 4, we propose robust circle criterion observers for a class of systems, that covers all our examples. We extended available results in the literature such that they can be synthesised for the neural mass models. The robustness of the designed state observers towards parameter uncertainty motivates the estimation of both parameters and states in Part II. In Chapter 5, we design an adaptive observer for a class of interconnected neural mass models. The convergence of the estimates is asymptotic. Finally, in Chapter 6, we present an alternative method using a multiple-model architecture, known in the literature as the supervisory framework. Under non-restrictive conditions, we guarantee the practical convergence of parameters and states.
Personalization of parliamentary behaviour: Conceptualization and empirical evidence from Belgium (1995–2014)

Personalization of parliamentary behaviour is an underexposed aspect of the broader personalization phenomenon. It is the aim of this article to first clarify the concept of personalization in the parliamentary arena, followed by a systematic investigation of the extent to which and under which circumstances this phenomenon takes place in the Belgian context. We develop four indicators that can be used to measure parliamentary personalization over time and across countries: a rise in the use of individual parliamentary instruments, an increase in single-authored initiatives for activities that could also be conducted collectively, a larger concentration of visible parliamentary activities and an increase in party switching. Our analysis based on an original data set of parliamentary activity in the Belgian House of Representatives (1995–2014) reveals that for none of these indicators a trend of personalization could be noted.
Enhancing Collaborative Group Processes to Promote Academic Literacy and Content Learning for Diverse Learners Through Video Reflection

Research indicates the benefits of collaborative learning for supporting academic literacy in content classrooms, especially for diverse and exceptional students such as students with learning disabilities or English learners (ELs) who can become disengaged in content classrooms if they struggle to access complex, content-related texts. Drawing from Cognitive Load Theory, we argue that collaborative group structures support students in sharing the load of processing these texts across all members, thus ensuring better comprehension of the content. Yet, collaborative structures may not be beneficial to diverse and exceptional learners in the group, particularly if students are not supported in how to engage successfully in collaborative work. Using a mixed-methods approach, we explored the use of video reflection and guided discussions with students using collaborative strategic reading (CSR) in heterogeneous collaborative groups in one seventh-grade general education, social studies class in an urban middle school. Students’ collaborative group work was video recorded pre- and post-reflection sessions to determine change in engagement in shared learning. The reflection session included students watching the video recording of their group work during CSR, discussing their collaboration using guided prompts, and setting goals for improvement. Following the reflection session, findings revealed an overall increase in time on task for all students, with increased participation of diverse and exceptional students in richer content-related discussions. When all students understand how the collaborative group shares the cognitive load and supports each other through discussing and elaborating on ideas, academic literacy and richer understanding of the content can occur.
Use of the XFEM for the design of adhesively-bonded T-joints

The use of adhesive bonds greatly increased in industrial applications, as they have multiple advantages compared to other more traditional bonding methods (fastened, welded and riveted joints). The number of approaches to predict the strength of adhesive joints has increased over the years. The eXtended Finite Element Method (XFEM) is a recent variant of the (Finite Element Method) FEM to model damage growth in structures, although it is yet seldom studied within the context of bonded joints. This work consists of an experimental and XFEM analysis of aluminium alloy T-joints, adhesively-bonded with three adhesive types. A parametric study is undertaken regarding the curved adherends’ thickness (tP2), with values between 1 and 4 mm. The adhesives Araldite® AV138 (strong but brittle), Araldite® 2015 (less strong but moderately ductile) and the Sikaforce® 7752 (with the smallest strength but highly ductile) were tested. A comparative analysis between the different joints conditions was undertaken by plotting peel (sy) and shear (txy) stresses, and analysing the damage variable. The XFEM predictive capabilities were tested with different damage initiation and propagation criteria. It was found that, provided that the modelling conditions are properly set, accurate numerical results can be found.
Users’ Definition of Snapchat Usage. Implications for Marketing on Snapchat

ABSTRACT Despite its high popularity, Snapchat remains a mystery to many marketers. This study uses a mixed-methods approach to gain a thorough understanding of how users define Snapchat usage in terms of their cognitive processing and behavioral patterns. 14 core associations for Snapchat media usage were explored in focus groups, which were then converted into a consensus map using the concept map method (N = 96). Unlike previous studies, the findings suggest that Snapchat is not so much a medium for continuous communication with the consumer. Nevertheless, it can enrich relationships with them. Media usage is determined by hedonistic goals, while rational goals and normative constraints are in the background. Marketers should therefore focus their attention on aesthetic, affective and alternating stimuli.
Augmented reality in logistics: qualitative analysis for a managerial perspective

Immersive technologies, namely virtual and augmented reality, are witnessing a growth in popularity, especially in creative fields, like videogames and film businesses. These technologies can also be effectively applied in other industrial sectors and their use can foster value creation and enhance efficiency and effectiveness, in a managerial perspective. The applications of augmented reality are analysed within the industrial field of logistics, according to three directives: training, operations and transport. A qualitative analysis is carried on to identify potential uses in this (and related) fields and a managerial perspective are proposed, identifying specific KPIs and heuristics for the three aforementioned areas. Results from the literature, field analysis and classification through KPIs point to effective utilisations of AR in logistics, both for training new (and often temporary) resources and in specific and core operations, like picking in warehouses and transport of goods.
Transmission of Han Pictorial Motifs into the Western Periphery

This paper examines the ways in which Fuxi and Nüwa were depicted inside the mural tombs of the Wei-Jin dynasties along the Hexi Corridor as compared to their Han counterparts from the Central Plains. Pursuing typological, stylistic, and iconographic approaches, it investigates how the western periphery inherited the knowledge of the divine pair and further discusses the transition of the iconographic and stylistic design of both deities from the Han (206 BCE–220 CE) to the Wei and Western Jin dynasties (220–316). Furthermore, examining the origins of the migrants on the basis of historical records, it also attempts to discuss the possible regional connections and migration from different parts of the Chinese central territory to the western periphery. On the basis of these approaches, it reveals that the depiction of Fuxi and Nüwa in Gansu area was modelled on the Shandong regional pattern and further evolved into a unique pattern formed by an iconographic conglomeration of all attributes and other physical characteristics. Accordingly, the Shandong region style not only spread to surrounding areas in the central Chinese territory but even to the more remote border regions, where it became the model for funerary art motifs. Based on both approaches, it reveals that the depiction of Fuxi and Nüwa in Gansu area was modelled on the Shandong regional pattern and further evolved into a unique pattern of an iconographic conglomeration of all attributes and other physical characteristics. Accordingly, the Shandong region style not only spread to surrounding areas in the central Chinese territory but even to the more remote border regions, where it became the model for funerary art motifs.
Exploring the relationships of Email Overload, Stress and Burnout in Social Workers

OF THE DISSERTATION Exploring the Relationships of Email Overload, Stress, and Burnout in Social Workers By Lisa M. Lowrie Kutztown University/Millersville University, 2019 Kutztown, Pennsylvania Directed by Dr. Alex Redcay Technostress is the inability to cope with information and communication technology which may result in stress and burnout. Email overload, stress, and burnout among social workers is a phenomenon that may impact retention in social and human service organizations. This mixed methods design uses the transactional theory of stress as the theoretical framework for measuring the relationship of email overload (email invasion, email volume, and email rapid response expectation) to stress and burnout in the social work workforce. This dissertation also explores generational cohort, gender, and social work degree as predictors of email overload. Participants in this study were social workers recruited through one of three membership organizations: Juvenile Detentions Centers and Alternative Programs (JDCAP), National Partnership for Juvenile Services (NPJS), and the Pennsylvania Council for Children, Youth, and Family Services (PCCYFS). Students enrolled at Kutztown University were also included in this study. There were 119 (N=119) participants that completed the email overload survey and six (N=6) participants that were interviewed. The findings of the study show that email overload was statistically significant and GenXers and Millennials reported higher levels of stress, anxiety and depression, and poor coping than that of the Boomer generational cohort. Further studies on email overload and technology overload may provide a basis for needed technology self-care strategies for social workers.
THE DEVELOPMENT OF PVDF/PEI BLENDED MEMBRANE: EFFECT OF STIRRING TIME ON MEMBRANE CHARACTERISTICS AND PERFORMANCE

The increased characteristics and performance of polyvinylidene fluoride (PVDF) membrane were investigated using polyetherimide (PEI) as a high-performance co-polymer for increased porosity, mechanical strength, PWF and thermal also chemical stability. The blend solution was prepared using a composition 2%PVDF/12%PEI/84%NMP/2%PEG-6000 (wt.%) with varying stirring time (7h, 12h, 16h, and 20h). The formation of a solid PVDF/PEI membrane was obtained using a non-solvent induced phase inversion (NIPS) method. Analysis of physical (surface and cross-section morphology, porosity, pore size) and mechanical (Young's modulus) characteristics, performance (PWF), thermal and chemical stability of the blended membranes were performed to evaluate the significance of stirring time effect. The resulting infrared spectra have confirmed the formation of PVDF/PEI blended membrane. All PVDF/PEI blended membranes were found to have symmetric structures with porosity 6.17% 30.64% and pore size 0.204 nm – 0.366 nm. The increase in mechanical strength can be seen from changes in Young's modulus values as the stirring time increases up to 12 hours. However, the stirring time for 16 and 20 hours resulted in a cast solution with too high viscosity resulting in a defect in the casting film using the automatic-casting knife. Increasing the homogeneity of PVDF/PEI cast solution as increasing stirring time has led to PEI characteristic properties that are capable of producing high PWF. This PVDF/PEI mixing method is a potential solution to obtain higher PVDF thermal stability and PEI chemical resistance.
Conducta Pro-Social en Ratas

In recent years, prosocial behavior has become an interesting topic within cognitive sciences. It was accepted that humans are the only ones with prosociality actions. However, recent experiments with rats have challenged that view. The present article reviews the experimental tasks recently developed to study prosocial behavior in rats. In addition, the present article discussed the findings of those experiments in order to assess whether empathy is the mechanism that underlies prosocial behavior in rats.
Implementation Intentions for Improving Self-Regulation in Multimedia Learning: Why Don’t They Work?

Abstract Learners face several self-regulatory challenges during multimedia learning: choosing adequate cognitive strategies (cognitive self-regulation), relying on their own learning abilities (motivational self-regulation), and investing sufficient effort (behavioral self-regulation). Implementation intentions (plans that help transform intentions into action) can support self-regulation. We expected that cognitive, motivational, or behavioral implementation intentions improved learning, compared to a control group. In a first experiment, we found weak evidence that cognitive and behavioral implementation intentions improved learning, whereas motivational implementation intentions reduced learning. However, replication failed in two follow-up experiments. Our findings contradict previous research and suggest that implementation intentions are not suitable to support multimedia learning. Future research should focus on possible boundary conditions that could account for the unexpected and unstable findings.
Early family experiences, narcissistic traits and adjustment in emerging adulthood

Exposure to risky family environment during childhood affects diverse mental health outcomes in adulthood. Recent studies have found associations between narcissistic personality traits and retrospective accounts of early experiences. However, it is important to distinguish between two forms of narcissism: the grandiose (characterized by grandiosity, aggression, and dominance) and the vulnerable narcissism (characterized by a defensive and insecure grandiosity that obscures the feelings of inadequacy, incompetence and negative affect) because some aspects of narcissism are more strongly related to psychological wellbeing than others. Therefore, our goal was to examine the relationship between early risky family experiences, individual’s narcissistic traits and adjustment in emerging adulthood. Moreover, we wanted to examine narcissistic vulnerability and grandiosity as possible mediators between early risky family experiences and current adjustment (wellbeing and distress). Data were collected on a total of 348 university students in Croatia (294 females, Mage = 21.57, SD = 2.91) in an online study. The hypothesized mediation model was tested using path analysis and showed good fit to the data. Early risky family experiences positively predicted both grandiose and vulnerable narcissism, and also directly negatively predicted one’s personal wellbeing and positively one’s distress. Furthermore, vulnerable narcissism positively predicted distress and negatively predicted one’s wellbeing, while grandiose narcissism did not predict any indicator of adjustment. Therefore, the hypothesis regarding the mediating role of narcissistic traits was only partly confirmed. In sum, the results show theoretically meaningful connections between
Earthfill dam seepage analysis using ensemble artificial intelligence based modeling

In this paper, an ensemble artificial intelligence (AI) based model is proposed for seepage modeling. For this purpose, firstly several AI models (i.e. Feed Forward Neural Network, Support Vector Regression and Adaptive Neural Fuzzy Inference System) were employed to model seepage through the Sattarkhan earthfill dam located in northwest Iran. Three different scenarios were considered where each scenario employs a specific input combination suitable for different real world conditions. Afterwards, an ensemble method as a post-processing approach was used to improve predicting performance of the water head through the dam and the results of the models were compared and evaluated. For this purpose, three methods of model ensemble (simple linear averaging, weighted linear averaging and non-linear neural ensemble) were employed and compared. The obtained results indicated that the model ensemble could lead to a promising improvement in seepage modeling. The results indicated that the ensembling method could increase the performance of AI modeling by up to 20% in the verification step.
Novice EFL Teacher Perceptions on their Past Mentoring Experience

This qualitative case study examines the perceptions of three novice EFL teachers regarding their past mentoring experiences in school settings. Semi-structured interviews were conducted to elicit their overall views as well as obtain insight to specific aspects of this process according to the Five Factor Model on Mentoring (Hudson, 2007). Findings indicate that the personal attributes of mentors were perceived as being most relevant. However, based on the perception of the teachers, aspects such as school requirements and feedback are not widely considered by their mentors despite the fact that these elements impact the mentoring process. It is expected that by analyzing teacher perceptions, more knowledge will be gained about future EFL student teacher preparation so that programs will be able to better address the specific needs of mentees during their practicum period.
The Weiss judgment: The Court’s further clarification of the ECB’s legal framework: Case C-493/17 Weiss and others, EU:C:2018:1000

In December 2018, the Grand Chamber of the European Court of Justice delivered its judgment in the Weiss case. This case is the most recent development in the Euro crisis case law. The financial crisis has shown the difficulty in determining the precise limits to the mandate of the European Central Bank. The Gauweiler case provided a legal framework but also left unanswered questions. This contribution will first provide the background to the Euro crisis and the context of the case then continue by giving a short summary and analyses of the Opinion of the Advocate General and the judgment of the Court. Finally, a reflection will be given on what lessons can be taken from the Weiss case. As the Weiss case appears to be last in Euro crisis case law, this reflection will include an overall analysis of the current interpretation of the mandate of the European Central Bank post-Euro crisis.
Smart as a Bug: A Computational Model of Learning in the Moth Olfactory Network, with Applications to Neural Nets

Smart as a Bug: A Computational Model of Learning in the Moth Olfactory Network, with Applications to Neural Nets Charles Boise Delahunt Co-Chairs of the Supervisory Committee: Professor J. Nathan Kutz Applied Mathematics Professor Eve Riskin Electrical Engineering The moth olfactory network is one of the simplest biological neural systems capable of Learning. It is thus ideal for exploring how learning occurs. The network, which includes the antenna lobe, mushroom body, and ancillary structures, contains several key structural motifs widespread in biological neural systems and of great interest. These include cascading networks, large dimension shifts from stage to stage, high-dimensional sparse codings of data, randomness, Hebbian (“fire together, wire together”) plasticity, and octopamine stimulation as a vital part of the learning mechanism. While these components are widespread in natural neural systems, they are largely absent from the engineered neural nets of machine learning. This thesis has three goals: To characterize the various components of the moth’s olfactory system and how they enable it to learn; to port the moth’s “bag of tricks” to machine learning contexts; and to examine learning as an injury mitigation mechanism. Our approach is to build a full computational model of the moth olfactory system with the following properties: Its structure and mechanics are tightly tethered to current knowledge of the moth olfactory system; its behavior statistically matches experimental data; and it is able to robustly learn new odors. To our knowledge this is the first full neural network model that is tightly tied in structure and behavior to a real biological system, and that also demonstrates learning behavior. From a Biology perspective, the model is a valuable platform to examine how key structural features enable learning in nature. For example, we analyse the role of octopamine stimulation and the functions of high-dimensional sparse network stages in learning. The model also allows predictions about structural details of the olfactory system that are not currently well-characterized. In addition, we explore the role of learning, and other structural features, as injury mitigation mechanisms. From a Machine Learning perspective, the model allows us to identify promising structures and tools that can be ported to ML systems. For example, it offers bio-mimetic solutions to two open concerns in human-built Neural Nets: It uses a biologically-plausible optimization method to train the network, potentially bridging a long-standing gap between natural and human-built neural nets; and it requires few training samples, offering a potential means to address a current bottleneck in use of neural nets, viz their vast appetite for training data.