Scientific Research Projects Research Articles

“They Really Only Look for the Best”: How Young People Frame Problems in School‐to‐Work Transition

This article presents how young people in educational measures experience and discuss tensions between structural and individualised challenges they face in the transition from school to work. The findings are based on an Austrian citizen social science research project that involved conducting participatory research in Vienna with 33 young people between the ages of 15 and 23 years who are in measures for early school leavers that are preparing for further education and training. These co‐researchers struggle with constant comparisons to “norm” biographies and their accompanying social pressure as they try to meet the high expectations of school, work, and family. Additionally, mental health was a prominent issue, as the young co‐researchers experience stigma and a lack of professional support, which can impede their access to the labour market. The results of our research indicate that young people in employment measures require a more inclusive school and work environment that supports them regardless of their origin, family background, appearance, or mental health status. They negotiate the tension between individual employability and structural disadvantage and demand a recognised place in society, a request that connects to current debates concerning the individualisation of transitions from school to work.

Dynamic Disease Screening by Joint Modelling of Survival and Longitudinal Data

AbstractSequential monitoring of dynamic processes is an active research area because of its broad applications in different industries and scientific research projects, including disease screening in medical research. In the literature, it has been shown that dynamic screening system (DySS) is a powerful tool for sequential monitoring of dynamic processes. To detect a disease (e.g. stroke) for a patient, existing DySS methods first estimate the regular longitudinal pattern of certain disease predictors (e.g. blood pressure, cholesterol level) from an in-control (IC) dataset that contains observations of a group of non-diseased people, and then compare the longitudinal pattern of the observed disease predictors of the given patient with the estimated regular longitudinal pattern. A signal of disease occurrence is triggered if their cumulative difference exceeds a certain level, facilitated by a built-in control chart. In practice, a dataset containing longitudinal observations of the disease predictors of both non-diseased and diseased people is often available in advance, from which it is possible to explore the relationship between the disease occurrence and the longitudinal pattern of the disease predictors. This relationship should be helpful for disease screening. In this paper, a new DySS method is suggested based on this idea. Numerical studies confirm that it can improve the existing DySS methods for disease screening.

Minerals for future technologies: how Germany copes with challenges

Abstract Energy transition, de-carbonization and the future of manufacturing will not end the import dependency of Germany's national economy, but it will most probably result in a shift to new and different dependencies. The need for new raw materials is rapidly increasing. Domestic resources may contribute to but not entirely meet the evolving demand. The supply of new raw materials requires new approaches in exploration supported by sound science. Here, we report in a summarized way on recent results of scientific research projects on critical minerals. Mineral commodities that have important uses and no viable substitutes, yet face potential disruption in supply, are defined as critical to a nation's economic and national security. The main topics are the assessment of critical mineral potential in primary ore deposits and mining waste, exploration of the deep subsurface and thermal brines, bioleaching and deep sea mineral deposits. Raw material development and extraction are affected by environmental concerns, especially groundwater and soil, and societal aspects, such as fair trade in supply chains.

FC063: Serum and Urine Galectin-9, Ip-10 and Siglec-1 as Biomarkers of Disease Activity in Patients with Systemic Lupus Erythematosus Compared to Anca-Associated Vasculitis: A Longitudinal Study

Abstract BACKGROUND AND AIMS Galectin-9, interferon-inducible protein-10 (IP-10) and sialoadhesin (SIGLEC-1) are considered as potential biomarkers reflecting disease activity in patients with systemic lupus erythematosus (SLE). In this study, we aimed to investigate the association of serum and urine galectin-9, IP-10 and SIGLEC-1 with disease activity in patients with SLE. Also, we compared the results with ANCA-associated vasculitis (AAV) to test the specificity of the biomarkers. METHOD A total of 63 patients with active SLE (31 renal and 32 extrarenal) were included in the study. A total of 30 patients with inactive SLE (15 renal and 15 extrarenal), 17 with renal active AAV and 32 healthy volunteers were selected as control groups. Serum (s) and urine (u) levels of galectin-9, IP-10 and SIGLEC-1 were tested using ELISA. Urine levels of biomarkers were normalized by urine creatinine. RESULTS Of 142 participants, 109 (76.7%) were female and median age was 36 (28.75–48) years. Groups were comparable with regard to sex and age distribution except for AAV. In AAV group, seven patients (41.1%) were female and median age was 60 (48–65.5) years. Proliferative lupus nephritis (LN) (class III/III + V and IV/IV + V) were found in 22 patients with active renal SLE (70.9%), while 6 patients (19.3%) had pure class V and 3 (9.7%) had class II LN. Levels of sIP-10, uIP-10, sGalectin-9 and uSIGLEC-1 were significantly higher in the active SLE group compared to the inactive SLE group (sIP-10; P = 0.046, uIP-10; P < 0.001, sGalectin-9; P = 0.031 and uSIGLEC-1; P = 0.006); however, no differences were detected in the comparison of uGalectin-9 and sSIGLEC-1 between these two groups (uGalectin-9; P = 0.180 and sSIGLEC-1; P = 0.699). sIP-10 (P < 0.001), uIP-10 (P = 0.029) and uGalectin-9 (P < 0.001) were significantly higher in patients with active SLE compared to AAV (Table 1). Serum and urine galectin-9, IP-10 and SIGLEC-1 did not differ between patients with active renal and extrarenal SLE. Levels of sIP-10, uIP-10 and uSIGLEC-1 were correlated with SLE Disease Activity Index (SLEDAI). ROC analyses confirmed that sIP-10, uIP-10, sGalectin-9 and uSIGLEC-1 discriminated disease activity in SLE (Figure 1). Serum and urine levels of all biomarkers were retested in 41 of 63 patients (65%) with active SLE after a median treatment of 8 (5–22.5) months. At the time of the second tests, there was a significant decrease in disease activity as measured by SLEDAI [2 (0–4)] compared to the time of the first tests [10 (6–15.5)]. Comparison of sGalectin-9 levels between the sample at the time of active disease and remission showed a very significant decline (P < 0.001). uGalectin-9, sIP-10 and uSIGLEC-1 also decreased after treatment; however, the difference was not statistically significant. CONCLUSION sIP-10, uIP-10, sGalectin-9 and uSIGLEC-1 are associated with disease activity in SLE. None is able to discriminate active renal from active extrarenal disease. sIP-10 and uIP-10 are specific for active SLE compared to renal active AAV. sGalectin-9 may be a valuable biomarker to monitor response after treatment for active disease. Funded by Scientific Research Projects Coordination Unit of Istanbul University. Project number: TSA-2019–34 218.

Silencing of NILCO by Small Interfering RNA Effects MDR1 in Colon Cancer Cells

The aim of the study is to investigate the effect of silencing of NILCO by siRNA on the MDR1 gene, which plays a role in chemoresistance. Cells of the human colon cancer lines Caco‐2 and HT‐29 were cultured at 37˚C in DMEM supplemented with 5% FBS in a humid incubator with 5% CO2. Exponentially growing untreated Caco‐2 and HT‐29 cells were collected and plated (4 x 105/ well in 2 mL) 24 hours before transfection. Plated cells were treated with either double‐stranded siRNA targeting Notch1 mRNA, leptin mRNA, IL‐1 β mRNA, control siRNA, or Paclitaxel (PTX) alone, Notch1 siRNA+PTX, Leptin siRNA+PTX, IL‐1β siRNA+PTX. The siRNAs of Notch1, IL‐1β and Leptin, were applied to the cells at a final concentration of 30 nM, and the cells were transfected with siRNA for 48 hours. After transfection, 100 nM Paclitaxel chemotherapeutic agent for HT‐29 and 130 nM for Caco‐2 was applied to the cells. Cells were harvested for PCR analysis after treatment with PTX for 24 hours.According to our findings, MDR1 gene expression was significantly increased in the paclitaxel group compared to the control group (p<0.05). Silencing of Notch, leptin and IL‐1β decreased MDR1 gene expression compared with the control group, but it was not statistically significant. (p>0.05). However, our results indicated that Notch1 siRNA+PTX, IL‐1β siRNA+PTX and Leptin siRNA+PTX downregulated MDR gene expression in the Caco‐2 cell line compared with PTX alone treated group (p<0.01). In addition, MDR1 gene expression levels were significantly decreased in the Leptin siRNA+PTX and IL‐1β siRNA+PTX groups compared with PTX alone group in the HT‐29 cell line, but the decrease in the Notch1 siRNA+PTX group was not statistically significant. (p<0.01, p<0.05, p>0.05). In conclusion, knockdown of NILCO genes is effective in regulating MDR1 expression, which is a hallmark in chemoresistance.The present study was supported by Eskisehir Osmangazi University Scientific Research Projects (BAP) Coordination Unit (grant no. 202011D11).

Enhancing Mental Health, Well-Being and Active Lifestyles of University Students by Means of Physical Activity and Exercise Research Programs.

Mental disorders (e.g., depression) and sedentary behavior are increasing, also among emerging adults. One particular target group of emerging adults with high sitting times and vulnerability to mental disorders are university students. In particular, anxiety and depressive symptoms as well as stress symptoms are very common among university students. The present manuscript discusses whether physical activity and exercise interventions can help to promote the mental health of emerging adults such as university students. The manuscript will summarize current scientific evidence and based on this evidence, introduce an university-based scientific research project that investigates if physical activity, exercise interventions and acute bouts of exercise of low- to moderate intensity can buffer perceived stress, alleviate mental health symptoms and strengthen well-being (psychologically and physiologically) among university students by positively influencing depressive and anxiety symptoms, perceived stress and emotion perception, body awareness and subjective well-being including overall quality of life. The research project, its concept, multimethod approach, and first results from available studies are discussed in relation to current scientific evidence, health care needs and future developments. The results from the studies conducted within the research project so far and that are briefly summarized in this manuscript suggest that physical activity, mental health and well-being are positively related, also in university students as an important group of emerging adults. The results further suggest that exercise interventions comprising aerobic exercises of low- to moderate intensity may work best to improve mental health (alleviate depressive symptoms and perceived stress) among university students after a few weeks of intervention. In addition, acute bouts of certain types of exercises (yoga in particular) seem to be particularly effective in changing perception of bodily signals, cardiac activity and emotion processing immediately after the exercise. The results underscore the importance of systematic investigations of the combined examination of psychological and physiological factors that promote an active lifestyle and that strengthen mental health and well-being (psychologically and physiologically) among emerging adults such as university students.

Design and Evaluation of a Conversational Agent for Facilitating Idea Generation in Organizational Innovation Processes

Large numbers of incomplete, unclear, and unspecific submissions on idea platforms hinder organizations to exploit the full potential of open innovation initiatives as idea selection is cumbersome. In a design science research project, we develop a design for a conversational agent (CA) based on artificial intelligence to facilitate contributors in generating elaborate ideas on idea platforms where human facilitation is not scalable. We derive prescriptive design knowledge in the form of design principles, instantiate, and evaluate the CA in two successive evaluation episodes. The design principles contribute to the current research stream on automated facilitation and can guide providers of idea platforms to enhance idea generation and subsequent idea selection processes. Results indicate that CA-based facilitation is engaging for contributors and yields well-structured and elaborated ideas.

Bayesian analysis on non-resonant behavior of 12C + 12C fusion reaction at sub-barrier energies * *Supported by the National Natural Science Foundation of China (11635015, 11805280, U1732145, 11705285, U1867212, 11961131012), the Continuous Basic Scientific Research Project (WDJC-2019-13), the Young Talent Development Foundation (YC212212000101) and the Leading Innovation Project (LC192209000701, LC202309000201)

Controversies exist among experiments and theories on the factor of the astrophysical important reaction 12C + 12C for energies below 3 MeV. Only frequentist approaches have been used so far for data analysis, and the confidence levels or theoretical errors are not available from previous theoretical predictions. In this study, the Bayesian method is employed to provide theoretical predictions and its 1σ confidence level based on all the currently available experimental data for the first time. The improved coupled-channels model CCFULL-FEM implemented with the finite element method as well as the Markov chain Monte Carlo approach emcee are adopted to analyze the non-resonant behavior of this reaction. The posterior distribution of the Woods-Saxon potential parameters is investigated. Compared with the widely used frequentist method MIGRAD within the Minuit minimization program, the Bayesian method has a significant advantage for exploring the potential parameter space. When the existing experimental data measured down to subbarrier energies are considered, the potential parameters are constrained to a very narrow range, and the predictions of the factor showed no sharp decrease in the low-energy region.

The Use of Internet of Things and Cloud Computing Technology in the Performance Appraisal Management of Innovation Capability of University Scientific Research Team.

This study aims to speed up the progress of scientific research projects in colleges and universities, continuously improve the innovation ability of scientific research teams in colleges and universities, and optimize the current management methods of performance appraisal of college innovation ability. Firstly, the needs of the innovation performance evaluation system are analyzed, and the corresponding innovation performance evaluation index system of scientific research team is constructed. Secondly, the Internet of Things (IoT) combines the Field Programmable Gate Array (FPGA) to build an innovation capability performance appraisal management terminal. Thirdly, the lightweight deep network has been built into the innovation ability performance assessment management network of university scientific research teams, which relates to the innovation performance assessment index system of scientific research teams. Finally, the system performance is tested. The results show that the proposed method has different degrees of compression for MobileNet, which can significantly reduce the network computation and retain the original recognition ability. Models whose Floating-Point Operations (FLOPs) are reduced by 70% to 90% have 3.6 to 14.3 times fewer parameters. Under different pruning rates, the proposed model has higher model compression rate and recognition accuracy than other models. The results also show that the output of the results is closely related to the interests of the research team. The academic influence score of Team 1 is 0.17, which is the highest among the six groups in this experimental study, indicating that Team 1 has the most significant academic influence. These results provide certain data support and method reference for evaluating the innovation ability of scientific research teams in colleges and universities and contribute to the comprehensive development of efficient scientific research teams.

Collaborative capability building for critical infrastructure resilience: assessment and selection of good practices

Accidental and intentional disruptive events affecting Critical Infrastructure (CI) systems dramatically increase on a global scale and put pressure on governments and CI operators to further improve technical and organizational capacities for securing the continuity of service. Experts in the field call for collaborative approaches to manage CI interdependencies and mitigate domino effects, which amplify the impact of disruptions over space, time and social functions. This paper presents an integrated framework for the classification, assessment and selection of Good Practices (GPs) in the Critical Infrastructure Resilience domain—‘CRAFTER’, from the perspective of collaborative Emergency Management (EM) capability building. The GPs mainly come from local and national level actions and programs, emphasizing the importance of fostering collaborative processes among stakeholders. The study identified 53 GPs through a systematic analysis of available scientific literature and research projects in the CI domain, which were used in the development of the CRAFTER framework. The framework was refined and validated through a questionnaire administered to CI experts, as a way to integrate theory-based and practitioner-based knowledge. The GPs were then classified and assessed according to their intended application context, the activities and functionalities covered, and the EM capabilities they support. The CRAFTER framework enables the assessment and benchmarking of GPs showing their strengths and weaknesses when used to build EM capabilities. It also supports practitioners in selecting a smallest effective bundle of GPS under different institutional and operational contexts, making sure that all the EM phases and capabilities are adequately covered.

Genome Sequence Resource of Sarocladium terricola TR, an Endophytic Fungus as a Potential Biocontrol Agent Against Meloidogyne incognita.

Genome Sequence Resource of Sarocladium terricola TR, an Endophytic Fungus as a Potential Biocontrol Agent Against Meloidogyne incognita.

Development of a Predicting Model for Calculating the Geometry and the Characteristic Curves of Pumps Running as Turbines in Both Operating Modes

This article is part of a scientific research project dedicated to the study of plants generating electricity from hydraulic sources by exploiting the technology of inverted flow centrifugal pumps, also known as PAT. The main purpose is to provide a contribution to the methodologies already existing in the literature, creating a one-dimensional model capable of predicting the characteristic curves of the machine, in both operating modes, without knowing its geometry. The first part of the work is therefore focused on the description of the fluid dynamic model, capable of determining the losses in the various sections of the machine, using different calculation approaches. The development of this model was carried out using a set of six centrifugal pumps, measured at the DIMEG Department of the University of Calabria and at the University of Trento. For this range of pumps, the characteristic curves were therefore obtained, both in pump and turbine operation. The second part of this work focuses on the description of the geometric model, useful as generally few data are provided in the manufacturer’s catalog, which is necessary for the correct installation of the machine. The geometric model can determine, using these parameters and through good design techniques and statistical diagrams, the entire geometry of the machine. This model refers to a pump prototype, having a simplified geometry, for which the characteristic curves of the PAT are obtained in pump operation. These curves are compared with those present in the manufacturer’s catalog, and if they show too high deviations, it is possible to act on some geometric parameters, chosen based on a sensitivity analysis. Once satisfactory results have been obtained, it is possible to obtain the characteristic curves also in turbine operation. This procedure has been finally applied to another PAT, taken as an example.

Artist-in-Residence: Christian Kosmas Mayer

In the first part of the interview, we take a closer look at what Christian Kosmas Mayer has got up to as artist-in-residence at the Schaufler Lab@TU Dresden and discuss his conviction that recent developments in genetic engineering and AI actually have their roots in the timeless human desire for immortality. The second part of the interview focuses on Mayer’s latest project Maa Kheru, which has attracted considerable attention. The artist initiated a scientific research project with the ultimate goal of recreating the voice of a 2000-year-old mummy using data from CT scans and then composed an 8-channel sound piece from audio recordings of its vocalizations.

Status and influencing factors of nursing and midwifery professionals' core competence- a cross sectional study.

This study aims to understand the current situation and multiple factors affecting the core competence specializing in the maternal, neonatal and under-five nursing in China. Highly skilled nurses and midwives are essential worldwide for achieving the Sustainable Development Goals, especially in low- and middle-income countries like China, due to the overwhelming COVID-19 crisis. The 890 nurses and midwives from 12 hospitals were investigated in this cross-sectional study, with two questionnaires: the sociodemographic information and competency inventory for the registered nurses. The participants reported a mean total score of 193.78 (±42.19) out of 220 and lowest in critical thinking and research ability (3.01 ± 0.82). The professional title, level, marital status, relationship quality, highest qualification, experience in specialist nurse training, participation in scientific research projects and publishing papers were the influencing factors (P < .05). The respondents' core competence needs improvement, especially critical regarding thinking and research ability. In addition, marriage and good or excellent relationship quality are factors that can potentially improve competence. Targeted interventions for higher core nursing competence need to be implemented, especially focusing on nurses' marital status and emotional support from partners.

GXP: Analyze and Plot Plant Omics Data in Web Browsers.

Next-generation sequencing and metabolomics have become very cost and work efficient and are integrated into an ever-growing number of life science research projects. Typically, established software pipelines analyze raw data and produce quantitative data informing about gene expression or concentrations of metabolites. These results need to be visualized and further analyzed in order to support scientific hypothesis building and identification of underlying biological patterns. Some of these tools already exist, but require installation or manual programming. We developed “Gene Expression Plotter” (GXP), an RNAseq and Metabolomics data visualization and analysis tool entirely running in the user’s web browser, thus not needing any custom installation, manual programming or uploading of confidential data to third party servers. Consequently, upon receiving the bioinformatic raw data analysis of RNAseq or other omics results, GXP immediately enables the user to interact with the data according to biological questions by performing knowledge-driven, in-depth data analyses and candidate identification via visualization and data exploration. Thereby, GXP can support and accelerate complex interdisciplinary omics projects and downstream analyses. GXP offers an easy way to publish data, plots, and analysis results either as a simple exported file or as a custom website. GXP is freely available on GitHub (see introduction)

Understanding scientific literacy through personal and civic engagement: A citizen science case study

ABSTRACT Citizen science programs, which engage volunteers in varied aspeicts of scientific research projects, have been widely touted as a promising avenue for enhancing public scientific literacy and scientific civic engagement. The meanings volunteers make of citizen science experiences can influence the ways that scientific information is translated into action. This paper develops a conceptual framework for understanding scientific literacy in terms of personal and civic engagement with science. The framework is explored through a case study of citizen scientists’ reflections on their experiences in an ecologically focused citizen science program. Findings describe ways that participants drew on their citizen science experiences to use and produce science in and for personal and civic contexts. Implications for enhancing connections between citizen science and personal and civic engagement are discussed.

When Matthew met Matilda: the Argentinean gender gap in the allocation of science and technology public grants

ABSTRACT This article analyses the presence of the gender gap in the process of allocation of public grants for science and technology activity – the Matilda effect – in Argentina. The empirical approach is based on the Argentinean Scientific and Technological Research Projects programme (in Spanish PICT), the main national public grant for scientific and technological projects, for the period 2003–2015. Two manifestations of the Matilda effect are verified. First, entry barriers since female researchers have lower probabilities of being selected for the first time than their male counterparts. Then, persistency barriers are also demonstrated, given that being awarded when funded immediately before is only significant among male researchers. The gap is even larger for the case of science, technology, engineering and mathematics fields of science. The cumulative nature of the Matilda effect calls for deliberated public actions to reduce the gap since horizontal instruments tend to increase the biases over time.

Designing Personality-Adaptive Conversational Agents for Mental Health Care

Millions of people experience mental health issues each year, increasing the necessity for health-related services. One emerging technology with the potential to help address the resulting shortage in health care providers and other barriers to treatment access are conversational agents (CAs). CAs are software-based systems designed to interact with humans through natural language. However, CAs do not live up to their full potential yet because they are unable to capture dynamic human behavior to an adequate extent to provide responses tailored to users’ personalities. To address this problem, we conducted a design science research (DSR) project to design personality-adaptive conversational agents (PACAs). Following an iterative and multi-step approach, we derive and formulate six design principles for PACAs for the domain of mental health care. The results of our evaluation with psychologists and psychiatrists suggest that PACAs can be a promising source of mental health support. With our design principles, we contribute to the body of design knowledge for CAs and provide guidance for practitioners who intend to design PACAs. Instantiating the principles may improve interaction with users who seek support for mental health issues.

Domain Model Based Design of Business Process Architectures

A business process architecture (BPA) model depicts business processes in an organization and their relations. An artifact for generating BPA models is proposed as the outcome of a design science research project. The proposed artifact consists of a method (i.e., a set of concepts, a proposed notation, and a detailed procedure), which is termed the domain-based BPA (dBPA) method due to using domain models as a starting point. The dBPA method tackles issues of currently available approaches: lack of structured inputs, limited consideration of process relations types, and restricted use of industry-standard modeling languages. The paper formalizes the dBPA method and illustrates its application in the manufacturing industry. Evaluation of the dBPA method revealed that practitioners perceived it as useful to achieve its goal with the benefits of being objective and clear and allowing to create complete and understandable BPA models that enable the integration of processes and the software that automates them.

Designing Attentive Information Dashboards

Information dashboards are a critical capability in contemporary business intelligence and analytics systems. Despite their strong potential to support better decision-making, the massive amount of information they provide challenges users performing data exploration tasks. Accordingly, dashboard users face difficulties in managing their limited attentional resources when processing the presented information on dashboards. Also, studies have shown that the amount of concentrated time humans can spend on a task has dramatically decreased in recent years; thus, there is a need for designing user interfaces that support users attention management. In this design science research project, we propose attentive information dashboards that provide individualized visual attention feedback (VAF) as an innovative artifact to solve this problem. We articulate theoretically grounded design principles and instantiate a software artifact leveraging users eye movement data in real time to provide individualized VAF. We evaluated the instantiated artifact in a controlled lab experiment with 92 participants. The results from analyzing users eye movement after receiving individualized VAF reveal that our proposed design has a positive effect on users attentional resource allocation, attention shift rate, and attentional resource management. We contribute a system architecture for attentive information dashboards that support data exploration and two theoretically grounded design principles that provide prescriptive knowledge on how to provide individualized VAF. Practitioners can leverage the prescriptive knowledge derived from our research to design innovative systems that support users information processing by managing their limited attentional resources.