bluuebunny/crossref_metadata_2025 huggingface dataset:
Invisible Battlegrounds: The COVID-19 Chapter in U.S.-China Relations
Authors: Wang Zheng
Published: July 2024

This introductory chapter offers an overview of the COVID-19 pandemic's impact on U.S.-China relations. It introduces the main findings and recommendations of the chapters in the book, highlighting the war-like impacts and damages the pandemic has inflicted on the two countries in terms of separation and decoupling, information warfare and cognitive dissonance, as well as the stimulation of nationalist sentiments and anti-Asian racism. By providing an outline of the book's content, this chapter sets the stage for an interdisciplinary and multi-dimensional assessment of the pandemic's broad-reaching consequences on this bilateral relationship.
Contested Narratives: The COVID-19 Origins Debate and Its Implications for U.S.-China Relations
Authors: Huang Yanzhong , Best Lucy
Published: July 2024

More than four years into the pandemic, the debate over the origins of COVID-19 continues to strain U.S.-China relations. At the heart of this debate lies the question of whether the pandemic resulted from a lab leak or a zoonotic spillover. This chapter delves deep into the politicization of the origins debate and its repercussions for bilateral ties. It unpacks the divergent narratives in both countries, shedding light on how domestic politics and geopolitical tensions have become intertwined with these narratives to further erode mutual trust and precipitate communication and cooperation breakdowns between the two countries.
Data-driven Wireless Positioning
Authors: Stahlke Maximilian , Feigl Tobias , Kram Sebastian , Ott Jonathan , Seitz Jochen , Mutschler Christopher
Published: July 2024

Radio-based indoor localization is a crucial enabler for various tasks like robot navigation or quality assurance in industrial assembly. However, especially industrial environments often present challenging propagation conditions, with reflections, diffraction obstruction, and blockage. While traditional, lateration-based positioning algorithms can provide high accuracies in line-of-sight (LOS) conditions, signal blockages cause non-line-of-sight (NLOS) propagation and degrade the performance dramatically. To overcome this problems, recently artificial intelligence (AI)-driven localization algorithms have shown promising results and can provide robust and high localization performance in such challenging environments. In this chapter, we evaluate the performance of AI-models trained on radio fingerprints in various challenging industrial environments. We evaluate the accuracy and the effect of environmental changes on the localization performance and robustness. Our results show that environmental changes significantly degrade the performance, which leads to a high effort in maintenance, i.e., keeping the models up-to-date. We show how to combine classical lateration-based algorithms with data-driven models employing uncertainty estimation to reduce the the effort for initial deployment and maintenance for a more robust localization solution.
Self-Optimization in Adaptive Logistics Networks
Authors: Mehringer Julius , Neumann Ursula , Wagner Friedrich , Scholl Christopher
Published: July 2024

The spectrum of applications for AI is extremely broad, ranging from support for complex decisions and data-driven corporate strategies to the automation of everyday processes. In logistics networks, a plurality of decisions are to be made on a daily basis. Typically, those decisions are comprised of a combination of forecasting and optimization, forming the area of prescriptive analytics. In this chapter, we present two use cases for arriving at optimal decisions: the case of prescribing cost-optimal order policies for the stocking of spare parts, and the case of mixing raw materials to final products with varying raw material quality.
Process-aware Learning
Authors: Frey Christian M.M. , Rauch Simon , Stritzel Oliver , Buck Moike
Published: July 2024

Processes in companies are diverse and complex. The production of different products, inter- or intra-company logistic processes, or other serial event sequences within companies have one thing in common: they can be traced on the basis of a documentation of the individual process steps. Usually, companies have domain experts for each department’s processes who use their experience and knowledge to plan and control these steps. However, with increasing complexity and diversity of processes, efficient planning and control is becoming more difficult or even impossible for human decision makers. In the the focus of Process-aware Learning, information documented on the data side, which is contained in the flow and execution of any process, should be integrated into AI-enhanced models. This should be accomplished in a way that is useful and as interpretable as possible for non-expert users. These models are used to identify important factors influencing the process, various process key figures, or anomalies in the process, and, based on these insights, to make forecasts or recommendations for action tailored to the process flows.
Combinatorial Optimization
Authors: Krause Jan , Kuen Tobias , Scholl Christopher
Published: July 2024

Optimization is a fundamental topic in mathematics that deals with finding the best solution to a problem from a set of possible solutions. This chapter provides an overview of mathematical optimization, its main objectives, and the methods used to solve optimization problems. It also introduces basic problems such as the modeling of binary decision trees, the pooling problem, the clique problem, and flow models. It concludes with an outlook on online optimization and learning optimization methods, which represent promising areas of research in the field. Overall, this chapter serves as a useful introduction to mathematical optimization, its basic problems, and their practical applications. The chapter is based on a white paper from Bärmann et al. [2]
Identifying Core Practices as a Framework for Teacher Educators’ Cooperative Professional Development
Authors: Doetjes Gerard , Hatlevik Ida Katrine Riksaasen
Published: July 2024

Connecting different knowledge domains is one of the main problems in teacher education. This chapter showcases a cooperation between two teacher educators at the University of Oslo. The aim of the contribution is two-fold. We identify specific core practices that are highly relevant for foreign language teaching in schools. Based on our experiences, we also propose a cooperative model for teacher educator competence development using an investigative approach to core practices as a framework. Such a cooperative model can contribute to the creation of better connections between different teacher education domains and, by doing so, promote student teachers’ sense of coherence.
Epistemic Coherence in Teacher Education
Authors: Heikkilä Mirva , Hermansen Hege
Published: July 2024

This chapter presents the concept of epistemic coherence and discusses its implications for researchers and practitioners in teacher education. Epistemic coherence is conceptualized as an emergent achievement comprising two key components: a) student teachers creating relations between a range of knowledge resources or modes of knowledge production and b) student teachers creating personal relationships with professional knowledge. This analytical approach can help move beyond conceptualizations of a theory–practice gap and other dichotomies that characterize existing research on knowledge use in teacher education and serve to open up the black box of how knowledge relations are constructed in teacher education.
Exploring Finnish Student Teachers’ Perceived Coherence of their Teacher Education Program
Authors: Mikkilä-Erdmann Mirjamaija , Nummi Julia , Erdmann Norbert
Published: July 2024

Our study investigates how Finnish student teachers experience the coherence of their study program and self-efficacy in teaching. By coherence we mean a continuing process of striving for a consistent teacher education program in which linkages are created between different courses, different stages, as well as theoretical and practical parts of the program. (Canrinus et al., Journal of Curriculum Studies 49:313–333, 2017) In general, the challenge in teacher education is to find the balance between theory and practice during the program. Previous studies have indicated that a lack of coherence may result in fragmented knowledge and skills (e.g., Bain and Moje, Phi Delta Kappan 93:62–65, 2012) and even poor self-efficacy in teaching. The participants of this study are master’s level students from two universities located in southern Finland. They are taking part in either a subject or a classroom teacher education program. Finnish teacher education is a five-year master’s degree program. The teaching practices are integrated in the initial teacher education program. The instrument used in the study is based on previous studies (Canrinus et al., Journal of Curriculum Studies 49:313–333, 2017; Hammerness et al., Coherence and assignments in teacher education: Teacher education survey, University of Oslo Department of Teacher Education and School Research, 2014). In addition, we have included a section about self-efficacy in teaching (Tschannen-Moran and Hoy, Teaching and Teacher Education 17:783–805, 2001). Principle component analysis (N = 127) showed five types of program coherence: opportunity to enact practice, coherence between theory and practice, opportunity to analyze practice, vision of good teaching and self-efficacy. Our results reveal that Finnish student teachers perceive their program as quite coherent and feel prepared for the teacher profession. Minor differences between class and subject teachers were found. Finally, pedagogical conclusions are discussed.
Perceptions of Coherence among Teacher Education Students and Newly Qualified Teachers of Foreign Languages. An Exploratory Norwegian-German Study
Authors: Doetjes Gerard , Zaki Katja
Published: July 2024

Recent studies on coherence in teacher education draw attention to a process- and actors-oriented approach, considering not only the supply-side, i.e. questions of structural or curricular programs of teacher education institutions, but also the reception of these offers by teacher education students. Against this background, the following contribution covers an exploratory interview study among teacher students and newly qualified teachers (NQTs) of foreign languages in Norway and Germany that who were asked asked about their teacher education programs. The chapter starts with a sketch of the theoretical foundations, followed by an outline of the chosen methodology—a qualitative approach with semi-structured interviews in a transnational setting – and a discussion of selected findings. In this context, a comparison is made between different cohorts and locations of education in order to shed light on the importance of curricular differences and to deduce questions for further research.
Forschungstätigkeit, Organisationsformen und institutioneller Kontext
Authors: Pichler Rupert , Heinze Thomas
Published: July 2024

Der Beitrag diskutiert den Zusammenhang von Organisationsform, institutionellem Kontext und der konkreten Forschungstätigkeit außeruniversitärer Forschungseinrichtungen im 20. Jahrhundert. Hierzu bezieht er sich auf Erkenntnisse der fünfzehn Beiträge des vorliegenden Bandes. Es werden die zentralen Forschungsfragen vorgestellt, entlang derer die Beiträge abgefasst wurden, sowie die daraus verallgemeinerbaren historisch-soziologischen Befunde. Weiterhin wird ein konzeptuelles Schema zur Einordnung historischer Fälle vorgestellt. Das Ergebnis unserer Analyse lautet: Die Erneuerung der Forschung findet auf zwei Weisen statt. Entweder werden für neue Forschungsthemen und -gebiete neue Forschungseinrichtungen und teilweise neue Organisationsformen etabliert, oder ein wissenschaftlich erfolgreiches Thema oder Gebiet wird organisational in Form neuer Forschungskapazitäten expandiert.
Über das Fliegen zum Forschen: Das DLR-Institut für Physik der Atmosphäre im Kontext des 20. Jahrhunderts
Authors: Achermann Dania
Published: July 2024

Obwohl das Institut für Physik der Atmosphäre (IPA) erst 1961/62 unter diesem Namen eingerichtet wurde, begann seine institutionelle Geschichte bereits 1924 mit der Gründung der „Rhön-Rossitten-Gesellschaft“. Im Laufe des Jahrhunderts wandelte sich sowohl der Name der Institution, ihre Organisationsform, als auch der Charakter ihrer Aktivitäten mehrmals. Ihre Wurzeln liegen im Segelflug als sportliche und militärische Aktivität, womit ein Interesse an der Atmosphäre bereits gegeben war. Doch dass diese deutsche Einrichtung schließlich als Forschungsinstitut die Turbulenzen des 20. Jahrhunderts (mit Unterbruch) überdauerte, war keineswegs vorherzusehen. Die organisatorischen und inhaltlichen Veränderungen können als Überlebensstrategie verstanden werden, um auf jeweils neue politische, gesellschaftliche und technologische Herausforderungen zu reagieren, wie sie beispielsweise der Zweite Weltkrieg, der Kalte Krieg, neue Umweltprobleme oder technische Innovationen im Flugverkehr mit sich brachten. In diesem Beitrag werde ich die Gründung, die Auflösung, die Neugründung sowie die weiteren strukturellen Veränderungen angesichts politischer Umwälzungen besprechen und analysieren, wie und weshalb sich das Erkenntnisinteresse dabei veränderte. Damit steht die Beziehung zwischen politischen und gesellschaftlichen Faktoren, Forschungsinstrumenten und Organisationsform sowie der Einfluss dieser Kontexte auf die wissenschaftlichen Fragestellungen im Vordergrund.
Organisatorische Entwicklung und Organisationsmuster außeruniversitärer Forschung am Beispiel der JOANNEUM RESEARCH Forschungsgesellschaft
Authors: Kleinberger Klaus , Polt Wolfgang
Published: July 2024

Die JOANNEUM RESEARCH Forschungsgesellschaft ist heute die zweitgrößte außeruniversitäre Einrichtung im Bereich der angewandten Forschung in Österreich. Ihre Geschichte nachzuzeichnen ist deshalb interessant, weil sie den Versuch darstellt, auf regionaler Ebene die verschiedenen Entwicklungsphasen von Innovationssystemen durch entsprechende Entwicklungen von Forschungseinrichtungen zu unterstützen, und weil sie in Österreich den größten und bislang nachhaltigsten Versuch in diese Richtung repräsentiert. Ursprünge dieser Entwicklung finden sich bereits in den 1950er und frühen 1960er Jahren, als vom Land Steiermark finanzierte Forschungsvereine eingerichtet wurden. Ihr Ziel war es, die notwendige, aber kostspielige Forschungsinfrastruktur sowohl an den steirischen Hochschulen als auch für Anwendungen in der Landesverwaltung und für Unternehmen sicherzustellen. Ab Beginn der 1970er Jahre erweiterten sich deren Forschungsgebiete und die Anzahl der Institute nahm zu. Das Forschungszentrum Graz und die Forschungsgesellschaft Joanneum wurden als Dachorganisationen eingerichtet, ehe Ende der 1980er Jahre eine Neuausrichtung mit Gründung der heutigen JOANNEUM RESEARCH Forschungsgesellschaft mbH folgte. Mit einem Fokus auf angewandte Forschung und Technologieentwicklung nimmt diese heute eine wichtige Rolle im regionalen und nationalen Innovationssystem ein.
An artificial intelligence-based nerve recognition model is useful as surgical support technology and as an educational tool in laparoscopic and robot-assisted rectal cancer surgery
Authors: Kinoshita Kazuya , Maruyama Tetsuro , Kobayashi Nao , Imanishi Shunsuke , Maruyama Michihiro , Ohira Gaku , Endo Satoshi , Tochigi Toru , Kinoshita Mayuko , Fukui Yudai , Kumazu Yuta , Kita Junji , Shinohara Hisashi , Matsubara Hisahiro
Published: July 2024

Background

Artificial intelligence (AI) has the potential to enhance surgical practice by predicting anatomical structures within the surgical field, thereby supporting surgeons' experiences and cognitive skills. Preserving and utilising nerves as critical guiding structures is paramount in rectal cancer surgery. Hence, we developed a deep learning model based on U-Net to automatically segment nerves.

Methods

The model performance was evaluated using 60 randomly selected frames, and the Dice and Intersection over Union (IoU) scores were quantitatively assessed by comparing them with ground truth data. Additionally, a questionnaire was administered to five colorectal surgeons to gauge the extent of underdetection, overdetection, and the practical utility of the model in rectal cancer surgery. Furthermore, we conducted an educational assessment of non-colorectal surgeons, trainees, physicians, and medical students. We evaluated their ability to recognise nerves in mesorectal dissection scenes, scored them on a 12-point scale, and examined the score changes before and after exposure to the AI analysis videos.

Results

The mean Dice and IoU scores for the 60 test frames were 0.442 (range 0.0465–0.639) and 0.292 (range 0.0238–0.469), respectively. The colorectal surgeons revealed an under-detection score of 0.80 (± 0.47), an over-detection score of 0.58 (± 0.41), and a usefulness evaluation score of 3.38 (± 0.43). The nerve recognition scores of non-colorectal surgeons, rotating residents, and medical students significantly improved by simply watching the AI nerve recognition videos for 1 min. Notably, medical students showed a more substantial increase in nerve recognition scores when exposed to AI nerve analysis videos than when exposed to traditional lectures on nerves.

Conclusions

In laparoscopic and robot-assisted rectal cancer surgeries, the AI-based nerve recognition model achieved satisfactory recognition levels for expert surgeons and demonstrated effectiveness in educating junior surgeons and medical students on nerve recognition.
Greenwashing or Striving to Persist: An Alternative Explanation of a Loose Coupling Between Corporate Environmental Commitments and Outcomes
Authors: Kudłak Robert
Published: July 2024

In response to increasing concerns about environmental degradation, companies started to introduce actions that portrayed their attentiveness to these issues. This commitment, however, hardly translates into actual improvements in corporate environmental performance and outcomes, which leads to accusations of greenwashing. In this conceptual paper, I use the idea of loose coupling to offer an alternative explanation of the disconnection between corporate environmental commitments and outcomes. Whilst companies are often perceived as rational and well-integrated bureaucracies, they, in fact, consist of subassemblies that are simultaneously coupled and responsive yet hold a certain degree of separateness and independence. Such loose coupling isolates an organisation from the external environment and gives the external stimuli only limited access to the system, allowing an organisation to persist. Such an understanding of organisations indicates that greenwashing might result from loose coupling caused by causal indeterminacy as well as a fragmented external and internal environment.
Factors Associated with Fathers’ Mental Health Difficulties in an Australian Help-Seeking Sample
Authors: Ritorto Lucia , McMahon Grace , Wallace Carolyn , Bladon Samantha , Dent Jillian , Giallo Rebecca
Published: July 2024

Fathers are at increased risk of mental health difficulties such as depression during the first postnatal year, however little is currently known about the extent to which fathers experience symptoms of anxiety and stress, and the factors associated with these symptoms. This study aimed to: (1) investigate the extent to which fathers accessing support to strengthen their coparenting relationship through a community health organisation experience depressive, anxiety and stress symptoms during the first postnatal year, and (2) examine associations between a broad range of individual, child, and family factors and fathers’ depressive, anxiety, and stress symptoms during the first postnatal year. This study involved secondary analysis of routinely collected data from 170 fathers of children aged 0–12 months who were enroled in a coparenting intervention programme delivered by a community health organisation in Melbourne, Australia. Elevated symptoms of stress were reported by ~28% of fathers, while elevated symptoms of depression and anxiety were reported by ~26% and 16% of fathers, respectively. Multiple regression analyses revealed evidence for associations between reduced parental self-efficacy and higher depressive and stress symptoms, while infant regulation difficulties and increased interparental conflict were associated with higher levels of stress. This study highlights that fathers are at risk of mental health difficulties during the first postnatal year. Findings demonstrate the importance of undertaking a broad assessment of fathers’ mental health during the first postnatal year and provide important insights into individual, child, and family factors that may represent optimal targets for prevention and early intervention.
Debt and Desert
Authors: Carlsson Andreas Brekke
Published: July 2024

According to what may be called the Debt Model, blameworthiness is defined in terms of deserved suffering. The Debt Model has a significant implication: one is less blameworthy if one has experienced some of the suffering one deserves, and no longer blameworthy once one has experienced the full amount of suffering one deserves. Blameworthiness, according to the Debt model, is not forever. In recent papers, Clarke (2022) and Howard (2022) independently criticize the Debt Model and argue for the opposite conclusion: if one is blameworthy, one will remain blameworthy forever. In this paper, I respond to this criticism as well as a recent argument against the Debt Model from Tierney (2022). I then present a prima facie case for the Debt Model. I argue that Clarke’s attempt to accommodate the intuitions elicited by this and similar cases has unwelcome implications. I will end the paper with some remarks about what roles we want our conceptions of blameworthiness to play. If Clarke’s account were right, the fact that an agent is blameworthy would play a far less significant role in our moral life than we often tend to assume. The Debt Model, I will suggest, makes better sense of our blaming practices.
Repeat stereotactic radiosurgery for progressive vestibular schwannomas after primary gamma knife radiosurgery
Authors: Taori Suchet , Bin-Alamer Othman , Tang Anthony , Niranjan Ajay , Flickinger John C. , Hadjipanayis Constantinos G. , Lunsford L. Dade
Published: July 2024

Purpose

Limited data provides guidance on the management of vestibular schwannomas (VSs) that have progressed despite primary Gamma Knife radiosurgery (GKRS). The present article reports our long-term experience after repeat GKRS for VS with sustained progression after solely primary GKRS management.

Methods

A retrospective review of 1997 patients managed between 1987 and 2023 was conducted. Eighteen patients had sustained tumor progression after primary GKRS and underwent repeat GKRS. The median repeat GKRS margin dose was 11 Gy (IQR: 11–12), the median tumor volume was 2.0 cc (IQR: 1.3–6.3), and the median cochlear dose in patients with preserved hearing was 3.9 Gy (IQR: 3-4.1). The median time between initial and repeat GKRS was 65 months (IQR: 38–118).

Results

The median follow-up was 70 months (IQR: 23–101). After repeat GKRS, two patients had further tumor progression at 4 and 21 months and required partial resection of their tumors. The 10-year actuarial tumor control rate after repeat GKRS was 88%. Facial nerve function was preserved in 13 patients who had House-Brackmann grade 1 or 2 function at the time of repeat GKRS. Two patients with serviceable hearing preservation (Gardner-Robertson grade 1 or 2) at repeat GKRS retained that function afterwards. In patients with tinnitus, vestibular dysfunction, and trigeminal neuropathy, symptoms remained stable or improved for 16/16 patients, 12/15 patients, and 10/12 patients, respectively. One patient developed facial twitching in the absence of tumor growth 21 months after repeat GKRS.

Conclusions

Repeat GKRS effectively controlled tumor growth and preserved cranial nerve outcomes in most patients whose VS had sustained progression after initial primary radiosurgery.
Alcohol’s Harm to Others: Victim Data on Prevalence and Risk Factors in a Nationwide Population Survey
Authors: Roystonn Kumarasan , Koh Yen Sin , Sambasivam Rajeswari , Zhang Yunjue , Abdin Edimansyah , Chong Siow Ann , Lee Cheng , Ma Stefan , Chow Wai Leng , Subramaniam Mythily
Published: July 2024

Alcohol’s harm to others (AHTO) is a growing concern globally. Yet research in Asia, especially among multi-ethnic populations, remains scarce. This cross-sectional study utilized national population data from the Health and Lifestyle Survey, and aimed to assess the prevalence and risk factors associated with AHTO in Singapore. Among 6465 respondents, findings revealed a lower prevalence of reported harm from others’ drinking (9.6%) compared to Western countries. Notably, young people (aged 15–34 years); ethnic minorities (Indians and Malays); individuals who are separated, divorced, or widowed; and victims who are drinkers themselves (whether light or hazardous drinking) were more susceptible to AHTO. These results underscore the need for targeted interventions and policies to mitigate AHTO, considering its impact on individuals’ health, well-being, and societal costs. This study contributes to the understanding of AHTO in a Southeast Asian context, informing public health strategies to address alcohol-related harms beyond the drinker.
Felt something, hence it works: Merely adding a sensory signal to a product improves objective measures of product efficacy and product evaluations
Authors: King Dan , Auschaitrakul Sumitra , You Yanfen
Published: July 2024

Product efficacy is an important driver of product evaluation and product usage. This research examines how marketers can improve perceived and actual product efficacy. Given the managerial ease of adjusting product design, we demonstrate that adding a sensory signal (e.g., tingling, cooling, fizzing) to a product that promises positive outcomes would improve product evaluations and actual product efficacy. In five studies (and two additional studies reported in the Web Appendix), we show that sensory signaling (vs. nonsignaling) products elicit actual product choice and improve product evaluations, repurchase likelihood, recommendation likelihood, as well as objective measures of product efficacy (such as consumer performance). This occurs because the sensory signals make consumers feel a greater transfer of benefits to the body during product usage. We further demonstrate that the effect holds even when persuasion knowledge is activated. Together, this research provides important insights on product designs that benefit not only marketers but also consumers.
Firm Default Prediction by GNN with Gravity-Model Informed Neighbor Node Sampling
Authors: Minakawa Naoto , Izumi Kiyoshi , Murayama Yuri , Sakaji Hiroki
Published: July 2024

Firm default prediction is important in credit risk management and understanding economic trends. Both practitioners and academic researchers have long studied it. While traditional statistical methods such as discriminant analysis and logistic regression have been used recently, machine learning and deep learning methods have been widely applied. The graph neural network (GNN) is one of the latest applications of deep-learning approaches. With the use of GNNs, it is possible to reflect the non-linear relationships of features among neighboring companies around the target company, whereas ordinary machine learning and deep learning methods focus only on the features of the target company. However, when handling large-scale graphs such as inter-firm networks, it is difficult to apply vanilla GNNs naively. Although uniform neighbor node sampling is commonly used for large-scale graphs, to the best of our knowledge, no research has focused on better sampling methods for GNN applications for default prediction. From the practical viewpoint, it means which companies should be considered with priority for firm default prediction. In this study, we propose a novel gravity model-informed neighbor sampling method based on the estimated transaction volume by utilizing knowledge from econophysics. The scope of this research is to determine whether we can improve default predictions by considering neighboring companies with larger transaction amounts compared to ordinary uniform sampling. We also verified that the proposed method improves the prediction performance and stability compared to GNNs with other sampling techniques and other machine learning methods using real large-scale inter-firm network data.
IL-22 activates the PI3K-AKT pathway to promote colorectal cancer cell proliferation and metastasis
Authors: Ruan Hong-xun , Qin Xiao-ning , Huang Wei , Lin Lin
Published: July 2024

Background

Colorectal cancer (CRC) is a prevalent malignancy with high morbidity and mortality rates. Previous studies have demonstrated that interleukin (IL)-22 is involved in CRC progression; however, the exact mechanism remains unclear. This study aimed to investigate the effects of IL-22 on CRC cell proliferation and metastasis.

Methods

IL-22 levels in the serum and tissues of CRC patients were measured using enzyme-linked immunosorbent assay (ELISA). Cell counting kit-8 (CCK-8) assay was used to detect the viability of CRC (HCT116) cells treated with different IL-22 concentrations. Colony formation, Transwell invasion, and scratch assays were employed to assess the effects of IL-22 on cell proliferation, invasion, and migration. Western blotting was performed to measure the expression levels of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT), p-PI3K, p-AKT, E-cadherin, matrix metalloproteinase (MMP)-2, MMP-9, SNAI1, and TWIST1 in HCT116 cells treated with IL-22 or a PI3K inhibitor.

Results

ELISA results showed that the expression of IL-22 was significantly increased in the serum and tissues of CRC patients compared to controls. IL-22 treatment increased cell viability and colony formation in a concentration-dependent manner and enhanced cell invasion and migration. Western blotting analysis revealed that IL-22 stimulation upregulated p-PI3K and p-AKT expression, while total PI3K and AKT levels remained unchanged. Additionally, IL-22 also decreased E-cadherin expression and increased the expression of MMP-2, MMP-9, SNAI1, and TWIST1.

Conclusions

IL-22 activates the PI3K-AKT pathway and promotes HCT116 cell proliferation and metastasis. Targeting the regulation of the PI3K/AKT pathway may be a potential therapeutic strategy for CRC.
A Thermal Approach for Modeling Concrete Ablation During Molten Corium–Concrete Interaction
Authors: Khurshid Ilyas , Amidu Muritala A. , Hassan Mubashir , Faizan Muhammad , Afgan Imran , Addad Yacine
Published: July 2024

An accident in a nuclear power plant involving a reactor core meltdown could result in the instigation of molten corium, which is a mixture of nuclear fuel, claddings and structural components. In this paper, an enthalpy-porosity model is proposed to comprehensively analyze the ablation of concrete during the molten corium and concrete interaction process. The developed numerical model is an extension of the enthalpy-porosity model and is termed the CCEPM. The developed CCEPM computational fluid dynamics model can predict natural convection, melting and solidification. The developed model simplifies the complex phenomena of concrete ablation and melting by incorporating the multiregional approach. The model was implemented in OpenFOAM by developing a new solver that couples buoyant-driven natural convection and conjugate heat transfer solvers. The thermal modeling and heat transfer capabilities of the developed solver were verified against experimental data sets. Additionally, the effects of various boundary conditions, concrete thermal conductivities and decay heat intensities were analyzed to study their impacts on concrete ablation. We observed significant low concrete ablation and controlled temperature and velocity fields for the water-cooled boundary condition. Accordingly, the ablation of concrete decreased by 17% by imposing the water-cooled boundary condition. Similarly, when the thermal conductivity of concrete was decreased to 0.43 and 0.13 W/m.K, the ablation of the concrete decreased by 38% and 75%, respectively. Furthermore, early cooling of molten corium to decrease the decay heat was found to be an effective strategy for successfully mitigating concrete ablation by 20%.
Efficient simulation and valuation of equity-indexed annuities under a two-factor G2++ model
Authors: Günther Sascha , Hieber Peter
Published: July 2024

Equity-indexed annuities (EIAs) with investment guarantees are pension products sensitive to changes in the interest rate environment. A flexible and common choice for modelling this risk factor is a Hull–White model in its G2++ variant. We investigate the valuation of EIAs in this model setting and extend the literature by introducing a more efficient framework for Monte-Carlo simulation. In addition, we build on previous work by adapting an approach based on scenario matrices to a two-factor G2++ model. This method does not rely on simulations or on Fourier transformations. In numerical studies, we demonstrate its fast convergence and the limitations of techniques relying on the independence of annual returns and the central limit theorem.
Conversion of limonene to limonene diol over activated carbon supported Ti catalyst
Authors: Marin Maria Minodora , Biru Iuliana Elena , Stavarache Cristina Elena , Avramescu Sorin Marius , Vasilievici Gabriel , Marinoiu Adriana , Dumitru Marius , Devred Francois , Gaigneaux Eric M. , Verziu Marian Nicolae
Published: July 2024

A series of activated carbon supported Ti-3,3′-ethylen bis(3,4-dihydro-2H-1,3-benzoxazine) complex catalysts (denoted Ti-Bz (0.25)/AC, Ti-Bz(0.37)/AC, and Ti-Bz (0.5)/AC) was evaluated in the conversion of limonene to limonene diol using H2O2 as oxidant. The opening of oxazine ring as a step to the titanium complex formation was highlighted, as far as we are aware, for the first time, by NMR analysis. A range of characterization methods, including SEM–EDS, nitrogen physisorption, ATR-FTIR, and XRD, showed that the procedure used in the preparation of these materials was reproducible. Parameters affecting the catalytic performances in the production of limonene diol, such as reaction temperature, amount of catalyst tested, and its catalytic stability, were studied. Ti-Bz (0.5)/AC was the most performant catalyst leading to limonene diol yield of 36.7%. The recyclability of the catalyst was evaluated along three catalytic consecutive tests that showed no significant difference of performance compared with that of fresh catalyst.
Female Tendons are from Venus and Male Tendons are from Mars, But Does it Matter for Tendon Health?
Authors: McMahon Gerard , Cook Jill
Published: July 2024

Tendons play fundamental roles in the execution of human movement and therefore understanding tendon function, health and disease is important for everyday living and sports performance. The acute mechanical behavioural and physiological responses to short-term loading of tendons, as well as more chronic morphological and mechanical adaptations to longer term loading, differ between sexes. This has led some researchers to speculate that there may be a sex-specific injury risk in tendons. However, the link between anatomical, physiological and biomechanical sex-specific differences in tendons and their contributory role in the development of tendon disease injuries has not been critically evaluated. This review outlines the evidence surrounding the sex-specific physiological and biomechanical responses and adaptations to loading and discusses how this evidence compares to clinical evidence on tendon injuries and rehabilitation in the Achilles and patellar tendons in humans. Using the evidence available in both sports science and medicine, this may provide a more holistic understanding to improve our ability to enhance human tendon health and performance in both sexes.
Semi-analytical calculation model for friction of polymers on the example of POM ∣ PE-UHMW and steel ∣ PE-UHMW
Authors: Bergmann André , Sumpf Jens , Dallinger Niels , Moneke Martin , Golder Markus
Published: July 2024

In this paper, a semi-analytical calculation model for the coefficient of friction (COF) of single spherical protrusions is presented. It allows the prediction of the deformative friction part (μdef) and adhesive friction part (μadh) of the friction pairings steel ∣ polyethylene with ultra-high molecular weight (PE-UHMW) and polyoxymethylene (POM) ∣ PE-UHMW. The experimental studies included unlubricated friction tests, which served to determine the total COF (μtot), as well as tests being lubricated with silicone oil, from which μdef is obtained. Based on the verification tests, it could be shown that both states of lubrication result in the same deformation and that the relationship between the rear angle (ω) and μdef postulated in the calculation model is valid. Therefore, friction tests with segmented spheres were carried out, which allow a specific variation of the ω.

It can be concluded that for both pairings the μdef is generally of minor significance (approx. 1/3 μtot) and the influence of the μadh predominates (approx. 2/3 μtot) the friction process. Furthermore the μtot decreases with increasing contact pressure especially in the low pressure range and depends on the form of motion (continuous and discontinuous).
An analytical approach for an AI-based teacher performance evaluation system in Saudi Arabia’s schools
Authors: Almubarak Arwa , Alhalabi Wadee , Albidewi Ibrahim , Alharbi Eaman
Published: July 2024

Teacher performance evaluation is essential to a teacher’s primary responsibilities. This study investigates the process of evaluating teachers’ performance to provide a basis for planning an ongoing professional development program. AI-based systems present an opportunity for objective and reliable evaluations, facilitating the identification of areas requiring improvement and contributing to the overall enhancement of educational quality. Consequently, incorporating AI into evaluating teachers has become a research hotspot. This research proposes an analytical comprehensive AI-based system for teacher evaluation. Moreover, we introduce a novel analytical index system derived from the current adopted Key Performance Indicators (KPI) in the Ministry of Education in Saudi Arabia and an overall algorithm. This study is part of an integrated project to evaluate teachers’ performance using AI. To build our model, we are accurately determining the evaluative weights through 13 workshops held with 283 field experts. The main hypothesis is that the weights were evenly distributed. After studying them, we found they were relatively different by 0.1 to 0.3%. By analyzing T-KPI, we believe that our proposed index system could overcome the limitations of human-based assessments as it assigned appropriate AI techniques for each, thus ensuring accurate, reliable, and objective evaluation. This innovation would also economically impact rationalizing spending and reducing costs.
Chitosan and its Nanoform Regulates Physiological Processes and Antioxidant Mechanisms to Improve Drought Stress Tolerance of Vicia faba Plant
Authors: Dawood Mona Gergis , El-Awadi Mohamed El-sayed , Sadak Mervat Shamoon
Published: July 2024

Purpose: Drought stress is an important challenge to global food security and agricultural output. Dramatic and quick climate change has made the problem worse. It caused unexpected impacts on the growth, development, and yield of different plants. Hence, the ultimate yield does not fulfill the required demand. Understanding the biochemical, ecological, and physiological reactions to these pressures is essential for improved management. Chitosan applications have a wide prospect of addressing abiotic issues. Moreover, chitosan and chitosan nanoparticles have a positive impact on increasing plant tolerance to abiotic stress, like drought stress. The current research investigated the consequences of drought stress on the morpho-physiological and biochemical parameters of Vicia faba plants, a comparison of chitosan and chitosan nanoparticles, and their ameliorating capacity towards drought stress. Methods: A pot experiment was conducted to evaluate the beneficial role of either chitosan (0.5, 1.0, and 2.0 gL− 1) or chitosan NPs (10, 20, and 30 mgL− 1) in inducing the Vicia faba tolerance to drought stress (60% water field capacity). Results: Drought stress significantly affected vegetative growth parameters of the shoot system, photosynthetic pigments, and indole acetic acid, accompanied by significant increases in vegetative growth parameters of the root system, some chemical composition of dry leaf tissues (total soluble sugar, soluble protein, proline, phenolic compound, glutathione, α tocopherol), hydrogen peroxide, malonialdehyde, lipoxygenase, and antioxidant enzyme activities (catalase, peroxidase, superoxide dismutase, ascorbate peroxidase, glutathione reductase). All applied treatments. chitosan and chitosan nanoparticles, at all concentrations, improved plant tolerance to drought stress via increasing vegetative growth parameters, photosynthetic pigments, indole acetic acid, total soluble sugar, soluble protein, proline, phenolic compound, glutathione, α tocopherol, and antioxidant enzyme activities, accompanied by decreases in hydrogen peroxide, malondialdehyde, and lipoxygenase enzyme. It is worthy to mention that 20 mgL− 1 chitosan nanoparticles was the most optimal treatment either under well water conditions (90% water field capacity) or drought stress conditions (60% water field capacity). Moreover, it is obvious from these results that the response of bean plants grown under well watered conditions was more pronounced than that of those plants grown under drought stress conditions to 20 mgL− 1 chitosan nanoparticles. Conclusions: Hence, it can be concluded that chitosan and chitosan nanoparticles can mitigate the negative impacts of drought stress by improving the photosybthetic pigments, endogenous indole acetic acid, and osmolyte contents, as well as the non-enzymatic and enzymatic antioxidant compounds of the Vicia faba plant.
The effect of tethered bi-naphthyls on visible-light promoted alkene-alkene [2 + 2] cycloadditions
Authors: Hoch Matteo , Sparascio Sara , Cerveri Alessandro , Bigi Franca , Maggi Raimondo , Viscardi Rosanna , Maestri Giovanni
Published: July 2024

Dispersion interactions are ubiquitous weak interactions that can play a role in many chemical events. Tailor-made catalysts and additives can lead to more selective reactions by properly exploiting dispersion interactions. Although radical-π dispersion interactions are known to have an important stabilizing role, this concept has been so far overlooked in synthetic photochemistry. We recently proved that similar dispersion interactions can play a profound impact on several reactions involving an energy transfer step. We present herein a study on the co-catalytic effect of tethered bi-naphthyl derivatives on the visible-light-promoted alkene-alkene [2 + 2] cycloaddition. A library of tethered bi-naphthyl derivatives was prepared in order to evaluate the impact of the tether on the efficiency of the prototypical [2 + 2] cycloaddition. The best performing additives showed a dramatic effect on the efficiency of the cyclization, and a rationalization of their relative efficiency was carried out through DFT modeling. The best co-catalyst allowed one to isolate desired products in good to excellent yields even employing several challenging substrates. These results offer new tools to devise optimized [2 + 2] photocycloaddition methods and provide valuable information for the design of organic co-catalyst that can boost photochemical reactions by exploiting dispersion interactions.

Graphical abstract
Characteristics of composite briquettes produced from carbonized banana peels and waste glass
Authors: Nyakoojo Emmanuel Karakwita , Wakatuntu Joel , Jasper Eseru , Yiga Vianney Andrew , Kasedde Hillary , Lubwama Michael
Published: July 2024

Briquettes made from carbonized agricultural residues present sustainable material alternatives to wood charcoal and firewood for commercial and industrial applications. However, these briquettes are plagued by property weaknesses including low drop strength and thermal efficiency. Therefore, this study focuses on enhancing the physical, mechanical and thermal properties of composite briquettes produced from carbonized banana peels and waste glass. Composite briquettes comprised of banana peels biochar and waste glass powder (0%, 5%, 10%, 20%, 30%, 40%, and 50%) were developed, characterized, and evaluated using thermo-gravimetric analysis and bomb calorimetry to determine thermo-physical properties and higher heating values, respectively. The thermal efficiency and emissions (CO, CO2, and PM2.5) were assessed using the water boiling test and an emissions monitoring system. Proximate analysis revealed that moisture content, volatile matter, fixed carbon, and ash content of the developed briquettes ranged from 2.5 to 9.7%, 19.2 to 37.2%, 28.7 to 55.6%, and 7.2 to 44.9%, respectively. Drop strength for the briquettes was 84% without waste glass in the composite, increasing to 94–98% with waste glass included in the composite matrix. Higher heating values ranged from 20.1 to 35.8 MJ/kg. Thermal efficiency rose from 22% with no waste glass powder to 40% with 50% waste glass powder addition, while CO and CO2 emissions decreased from 41 to 11 ppm; and 50 to 15 ppm, respectively. PM2.5 remained constant across all banana peel biochar waste glass composites. Notably, even a modest 10% waste glass composition significantly improved drop strength and thermal efficiency, but higher waste glass percentages correlated with elevated ash values and reduced higher heating values. Therefore, the developed composite briquettes can be used in commercial and industrial applications including in some industrial boilers.
Optimized Forest Framework with A Binary Multineighborhood Artificial Bee Colony for Enhanced Diabetes Mellitus Detection
Authors: Pradhan Gaurav , Thapa Gopal , Pradhan Ratika , Khandelwal Bidita , Panigrahi Ranjit , Bhoi Akash Kumar , Barsocchi Paolo
Published: July 2024

Diabetes mellitus (DM) is a common chronic condition that mainly affects older adults. It's important to identify it early to prevent complications. Machine learning is essential for early detection of DM. This article introduces a new method for detecting DM using a random forest ensemble within an optimized framework. The optimized forest framework depends on finding the best DM features, which are identified using the binary multineighborhood artificial bee colony (BMNABC) technique. During preprocessing, the BMNABC algorithm efficiently identifies important features and then inputs them into the random forest within the optimized forest framework for accurate classification. Five modern DM datasets were used to validate the suggested model. The comparison of the proposed model with other leading models revealed significant insights. The BMNABC + ODF(RFE) model demonstrated exceptional proficiency in detecting diabetes mellitus (DM) across various datasets. It achieved an accuracy of 96.36% and a sensitivity of 99.95% on the merged dataset (130 US and PIMA images). The Iranian Ministry of Health dataset showed an accuracy of 97.28% and a sensitivity of 97.12%. In the Sylhet Diabetes Hospital dataset, the accuracy and sensitivity were 96.81% and 98.07% respectively. However, on the PIMA dataset, the model displayed a nuanced performance, with an accuracy of 77.21% and a sensitivity of 68.83%. Lastly, on the questionnaire dataset, the BMNABC + ODF(RFE) model achieved an accuracy of 96.43% and a sensitivity of 97.15%. These findings emphasize the model's ability to adapt and perform effectively in different clinical environments, outperforming other models in terms of accuracy and sensitivity in detecting DM.