bluuebunny/crossref_metadata_2025_split huggingface dataset:
“Gravettians in the Altmühl Valley”? Comprehensive Reassessment and New Data from the Sequence from the Abri I im Dorf (Neuessing, Bavaria, Germany)
Authors: Calvo Aitor , Pasda Kerstin , Rutan Nadja , Arrizabalaga Alvaro , Uthmeier Thorsten 
Published: July 2024

Abstract
Due to the high density of cave and rock shelter sites, the Altmühl Valley is one of the most essential regions of southern German Palaeolithic research. The site presented in this paper, the Abri I im Dorf, lies within the main concentration of Palaeolithic sites found in this valley, extending along its lowest stretch between Riedenburg and its confluence into the Danube in Kelheim. We present the results achieved in reassessing the archaeo-stratigraphic sequence uncovered during the excavation campaign of 1959, including the first radiocarbon dating and comprehensive analysis of the lithic, faunal and bone industry evidence. Radiocarbon evidence points to occupations dated to ca. 27 ka cal BP. At the same time, the features of the lithic assemblage (blade industry with a predominance of burins and an important presence of backed tools) fit those of Late/Final Gravettian technocomplexes in the Danube region. However, the characteristic evidence traditionally associated with these industries (Kostënki knives and shouldered points) is scarce and highly questionable. The same applies to the “shovel-like” ivory object, typically related to the Pavlovian but with a doubtful determination as a shovel and no clear parallels in this and other industries of Gravettian tradition. The faunal remains revealed that hunting activities, which occurred between late summer and the beginning of winter, concentrated on reindeer. Nonetheless, new excavations and analyses are required to confirm all these preliminary results. In this sense, future work at the Abri I im Dorf can significantly contribute to our understanding of pre-LGM human settlement dynamics in the Upper Danube.
Dispersive Wave Focusing on a Shear Current: Part 2—Nonlinear Effects
Authors: Zheng Zibo , Li Yan , Ellingsen Simen Å 
Published: July 2024

AbstractContinuing our recent work [Ellingsen et al., Water Waves (2024)] we investigate the influence of vertically sheared currents on the surface elevation as well as the kinematics of dispersively focusing wave groups up to second order in steepness. The groups are assumed long crested in deep water which may travel at oblique angles with the current, which has a depth-dependent profile in both magnitude and direction. A strong but realistic shear current affects the wave surface elevation only slightly but the wave-induced horizontal velocity beneath the point of focus is very significantly affected, and new phenomena occur at second order. Firstly, a shear current causes wave-induced superharmonic velocity to be nonzero, contributing significantly for moderate wave steepness. At linear order, following (opposing) shear causes horizontal velocities to be amplified (reduced); for crest-focused wave groups, the superharmonic contribution reduces the influence of shear, whereas for trough-focused waves the velocity change from linear and second-order waves add, causing a substantially larger shear-induced effect. Secondly, the sub-harmonic mean flow is not strictly a return flow, but can follow the direction of wave propagation at the depths nearest the surface. Thirdly, unlike the case without shear where the subharmonic mean flow vanishes in the limit of zero bandwidth, it can now tend to a finite value in the narrowband limit. The criterion for this to happen is that the shear current has nonzero curvature.
Fuzzy Logic Enhanced Second-Order Sliding Mode Controller Design for an Experimental Twin Rotor System Under External Disturbances
Authors: Ozer Hasan Omur , Hacioglu Yuksel , Yagiz Nurkan 
Published: July 2024

Abstract
Background
The twin rotor model is frequently studied by researchers because although it has a basic structure the coupled pitch and yaw motions are adequately represented. However, it is quite difficult to obtain an efficient controller due to external disturbances. Classical sliding mode controller (SMC), which is of first order, is recognized to be robust in case of parameter changes and external disturbances especially when the sliding motion takes place, but it possesses chattering in the control input which may damage the mechanical parts of the system.

Purpose
In this study it was aimed to design a robust controller without chattering effect which will be used for the control of the twin rotor system in real time experiments.

Methods
To remedy the chattering issue, a novel fuzzy logic enhanced second-order sliding mode controller (FSOSMC) based on super twisting algorithm is proposed. This controller suppresses chattering while enhancing the robustness of the controller where the sliding surface slope parameter is updated online via a fuzzy logic unit. Then the proposed controller is implemented on an experimental twin-rotor system which has highly nonlinear and coupled dynamics.

Results
Real time experiments were performed on the twin rotor system using the proposed FSOSMC. For comparison purpose the SMC and second-order sliding mode controller (SOSMC) were also applied to the same system. The results have shown that the proposed controller increased the tracking performance without increasing the control effort while reducing the chattering.

Conclusions
The experimental results verified the success of the designed FSOSMC, therefore it may be recommended for the robust and precise control of aerial vehicles.

Graphical Abstract
Sharing and Repairing at University: On Student Practices, and the Future of the Circular Campus
Authors: Hobson Kersty , O’Byrne Megan 
Published: July 2024

AbstractFor decades, Higher Education Institutions (HEIs) have added their names to multi-scale environmental declarations and programmes for action, such as UNESCO’s ‘Education for Sustainable Development’. More recently HEIs have incorporated key facets of the Circular Economy into their norms and practices. While such agendas often focus on waste management regimes and infrastructural issues, this paper argues that on-campus borrowing and repairing practices are pivotal to any ‘circular campus’ goals, particularly the practices of students. Yet, little is known about the current borrowing and repairing attitudes and behaviours of HEI attendees. In response, this paper discusses the results of a project at Cardiff University (Wales), which surveyed students about what they currently borrow and repair; what they would like to borrow and repair; and what stands in the way of them doing more. The results show that, despite popular discourse that young adults—in particular Generation Z—are the ‘sustainability generation’, results suggest their attitudes and practices align quite closely to the broader population trends as drawn from the extant literature, in terms of barriers to action and low engagement with formal sharing and repairing platforms and spaces. As such, this paper argues that forms of circular practices need to be incorporated into on-campus ‘activist learning’ to increase skills and confidence amongst students: and to work towards displacing the norms of high consumption lifestyles that students are starting to display.
Assessing the effects of different foundation base shapes on settlement and heaving in expansive clay: numerical analysis
Authors: Mohamed Walaa-Eldin Elsherif 
Published: July 2024

AbstractThis paper investigates the behavior of shallow foundations with different base shapes on expansive soils under various Stresses conditions and different slopes of the base. Expansive soils are soils that undergo significant volume changes due to variations in moisture content, which can cause severe damage to structures built on them. The shape of the foundation base can influence the magnitude and distribution of the soil pressures, as well as the deformation and cracking of the foundation. The paper presents a numerical analysis using a finite element method with Plaxis 3D. The paper also proposes some recommendations for the optimal design of foundation base shapes on expansive soils. The numerical results show that the foundation base shape has a significant effect on the stress and displacement distributions in the soil and the foundation and that some shapes perform better than others in terms of reducing the soil pressures. The paper provides some useful insights for the design and construction of shallow foundations on expansive soils.
Strategic view on the current role of AI in advancing environmental sustainability: a SWOT analysis
Authors: Greif Lucas , Kimmig Andreas , El Bobbou Sleiman , Jurisch Paul , Ovtcharova Jivka 
Published: July 2024

AbstractSustainability has become a critical global concern, focusing on key environmental goals such as achieving net-zero emissions by 2050, reducing waste, and increasing the use of recycled materials in products. These efforts often involve companies striving to minimize their carbon footprints and enhance resource efficiency. Artificial intelligence (AI) has demonstrated significant potential in tackling these sustainability challenges. This study aims to evaluate the various aspects that must be considered when deploying AI for sustainability solutions. Employing a SWOT analysis methodology, we assessed the strengths, weaknesses, opportunities, and threats of 70 research articles associated with AI in this context. The study offers two main contributions. Firstly, it presents a detailed SWOT analysis highlighting recent advancements in AI and its role in promoting sustainability. Key findings include the importance of data availability and quality as critical enablers for AI’s effectiveness in sustainable applications, and the necessity of AI explainability to mitigate risks, particularly for smaller companies facing financial constraints in adopting AI. Secondly, the study identifies future research areas, emphasizing the need for appropriate regulations and the evaluation of general-purpose models, such as the latest large language models, in sustainability initiatives. This research contributes to the growing body of knowledge on AI’s role in sustainability by providing insights and recommendations for researchers, practitioners, and policymakers, thus paving the way for further exploration at the intersection of AI and sustainable development.
Bioelectronic Delivery of Potassium Ions Controls Membrane Voltage and Growth Dynamics in Bacteria Biofilms
Authors: Dechiraju Harika , Li Yixiang , Comerci Colin , Luo Le , Figuerres Sydnie , Asefi Niloofar , Trevino Ansel , Barbee Alexie , Tebyani Maryam , Baniya Prabhat , Teodorescu Mircea , Süel Gürol , Rolandi Marco 
Published: July 2024

Abstract
Bioelectrical signaling, or bioelectricity, is crucial in regulating cellular behavior in biological systems. This signaling, involving ion fluxes and changes in membrane potential (Vmem), is particularly important in the growth of bacterial biofilm. Current microfluidic-based methods for studying bacterial colonies are limited in achieving spatiotemporal control over ionic fluxes due to constant flow within the system. To address this limitation, we have developed a platform that integrates biofilm colonies with bioelectronic ion pumps that enable delivery of potassium (K+) ions, allowing for controlled manipulation of local potassium concentration. Our study examines the impact of controlled K+ delivery on bacterial biofilm growth patterns and dynamics. We observed significant changes in Vmem and coordination within the biofilms. Furthermore, we show that localized K + delivery is highly effective in controlling biofilm expansion in a spatially targeted manner. These findings offer insights into the mechanisms underlying bacterial signaling and growth, and suggest potential applications in bioengineering, synthetic biology, and regenerative medicine, where precise control over cellular signaling and subsequent tissue growth is required.
Beyond therapeutic potential: a systematic investigation of ketamine misuse in patients with depressive disorders
Authors: Juneja Keshav , Afroze Sabah , Goti Zeel , Sahu Sweta , Asawa Shivani , Bhuchakra Hamsa Priya , Natarajan Balaganesh 
Published: July 2024

AbstractKetamine, a pharmacological agent that acts as an antagonist of the N-methyl-D-aspartate (NMDA) receptor, has garnered considerable interest because of its notable and expeditious antidepressant properties observed in individuals diagnosed with major depressive disorder (MDD) who exhibit resistance to conventional therapeutic interventions. A comprehensive and rigorous systematic review was undertaken to evaluate the prevalence of ketamine abuse undergoing ketamine treatment for depressive disorders. A comprehensive search was conducted across the electronic databases to identify pertinent studies published between 2021 and 2023. The present investigation incorporated a comprehensive range of studies encompassing the abuse or misuse of ketamine, including case reports, observational studies, and clinical trials. Data extraction and quality assessment were conducted in accordance with predetermined criteria. The findings of this systematic review demonstrate the importance of monitoring and addressing ketamine abuse in patients receiving ketamine treatment for depressive disorders like MDD. The wide range of reported prevalence rates highlights the need for standardized criteria and measures for defining and assessing ketamine abuse. This study presents a significant contribution to the field by introducing a novel screening questionnaire and assessment algorithm designed to identify and evaluate ketamine misuse among major depressive disorder (MDD) patients undergoing ketamine treatment. This innovative tool holds the potential to enhance clinical practice by providing healthcare professionals with a standardized approach to promptly detect and address ketamine misuse. The integration of this screening tool into routine care protocols can facilitate more effective monitoring and management of ketamine misuse in this population, ultimately leading to improved patient outcomes and safety.
Efficient Heart Disease Classification Through Stacked Ensemble with Optimized Firefly Feature Selection
Authors: Natarajan Krishnamoorthy , Vinoth Kumar V. , Mahesh T. R. , Abbas Mohamed , Kathamuthu Nirmaladevi , Mohan E. , Annand Jonnakuti Rajkumar 
Published: July 2024

AbstractIn the current century, heart-related sickness is one of the important causes of death for all humans. An estimated 17.5 million deaths occur due to heart disease worldwide. It is observed that more than 75% of peoples with average income level mostly suffer from heart diseases and its complications. So, there is need for predicting heart infection and its related complications. Data mining is the method of converting raw data into useful information. These tools allow given data to predict future trends. Data mining concepts were mainly adapted in heart disease data sets to interpret the intricate inferences out of it. In the modern world, many research are carried in health care engineering with the use of mining and prediction techniques. This investigation aims to identify significant features in heart disease dataset and to apply ensembling techniques for improving exactness of prediction. Prediction models are developed using different ensembling techniques like stacking and voting. For the experimental purpose, the Z-Alizadeh Sani dataset is used, which is available in the UCI machine learning data repository. Stacking and voting techniques are applied to the dataset. Stacking with substantial characteristics has the maximum accuracy of 86.79% in the Z-Alizadeh dataset. Test outcome proves that the prediction model implemented with the features selected using firefly algorithm and stacking-based classification model has the highest accuracy prediction than other technique. Furthermore, this study delineates a comparative analysis with prior works, showcasing the superior capabilities of the firefly algorithm in optimizing feature selection processes, which is crucial for advancing the accuracy of heart disease predictions.
Expressed preferences for public health education of students during COVID-19 vaccination intervention: a cross-sectional comparative study
Authors: Roy Debendra Nath , Azam Md.Shah , Islam Ekramul 
Published: July 2024

Abstract
Background
Public health education is a powerful tool for improving communicable disease awareness and prevention protocols. Despite the fact that health education is crucial for the advancement of COVID-19 awareness and vaccination decisions, how a teacher approaches students to learn about health education during COVID-19 vaccination is a challenging issue. This study aimed to assess the preferences for public health education during COVID-19 vaccination intervention and compare the predictors of preferences between science and non-science university students in Bangladesh.

Methods
A multi-item questionnaire was developed and an online link was conveniently sent to the encounters between 31st May, 2023 and 15th August, 2023. Binary logistic regression analysis was applied to rationalize the research objective.

Results
The pooled preference for public health education was 71.3% (95% Confidence Interval [CI] 67.7–74.3) vs. 81.5% (95% CI 79.3–84.7) between science and non-science students. Out of twelve predictors “vaccine agreement”, “bio-safety behavior", and “disease awareness” were significantly associated (p < 0.01, p < 0.05) with the preference for public health education in both groups. Varied effects were also observed for some predictors: vaccine “safety” and “side effects” were significant (p < 0.05, p < 0.01) in science and non-science students, respectively. To address the conflict in decisions, non-science students significantly preferred “prevention alliance” whereas science students preferred “environmental health” issues (p < 0.05).

Conclusion
Public health education was more preferred by non-science university students than by science students in making COVID-19 vaccine decisions . The focus of transformative public health education should be interdisciplinary, including information on communicable diseases, public health measures, and prevention alliances, as well as information about vaccines' side effects and safety.
A model for enhancing digital transformation through technology-related continuing professional development activities in academic libraries in context
Authors: Nakaziba Sarah , Ngulube Patrick 
Published: July 2024

AbstractThis paper is based on the findings of a doctoral study that aimed to examine the role of continuing professional development (CPD) in enhancing digital transformation in selected university libraries in Uganda. One of the ways of effecting digital transformation is to continuously build the technological competencies of the librarians working in academic institutions through attending technology-related CPD. The study adopted a mixed methods approach with a convergent parallel design for collecting qualitative and quantitative data from six universities in Uganda. Quantitative data were collected from 76 librarians with a minimum degree-level qualification from the six selected universities. Qualitative data were obtained from six University Librarians working in these universities. The study findings indicated several challenges hindering librarians from participating in technology-related CPDs such as lack of management support, lack of personal interest, limited funding, and lack of opportunities, among others. The implementation of digital transformation within university libraries in Uganda was also reported to be beset by a lack of competent staff, limited management support, lack of funds, and technological gaps. Therefore, this paper presents a proposed model to address challenges hindering the digital transformation and the participation in technology-related continuing professional development activities within academic libraries. The proposed model is based on the study findings, and it draws from Watkin and Marsick’s learning organisation model, andragogy theory, the technology-organisation-environment framework, and extant literature. The model will guide academic libraries in the implementation of a conducive environment to necessitate staff development and implementation of digital transformation.
Review on practice and challenges of ICT integration as pedagogical tools in Ethiopian primary school curriculum implementation
Authors: Gonfa Merga Hunde , Birhanu Asnake Lealem , Gendo Kemal Mohammed 
Published: July 2024

AbstractThese days' students are more comfortable with technology. Therefore, we need to start using technology in creative ways to make it less boring. The use of ICT in teaching has the potential to transform higher education. It's a dynamic approach to education. When compared to the conventional chalk and talk learning method, it offers additional advantages. For students, the entire educational process can occasionally seem tiresome. ICT use in the classroom is crucial in this digital age to provide students with the opportunity to acquire and apply the necessary 21st-century skills. Therefore, understanding the problems and difficulties associated with ICT use in education will help instructors get past these difficulties and become proficient users of technology. Since the introduction of information and communications technologies (ICT) into the classroom, educators have developed their perspectives about ICT's usefulness as a teaching tool, its impact on students' learning outcomes, and its influence on their self-assurance and competency. There are obstacles to ICT integration in education. Lack of time, resources, access, and technological help are some of the external obstacles that teachers must overcome.
Adaptive interior design method for different MBTI personality types based on generative artificial intelligence
Authors: Huang Zhaoxu 
Published: July 2024

AbstractAccurately predicting homeowners’ aesthetic preferences is crucial in interior design. This study develops a fine-tuning model (LORA) for interior design styles corresponding to different MBTI personality types, leveraging the Stable Diffusion Web UI platform and integrating it into a generative artificial intelligence framework. Subsequently, personalized aesthetic preference architectural interior renderings are recommended based on homeowners’ personality traits, aiming to achieve an adaptive interior design approach. To achieve more precise adaptive solutions, this research surveys the style and color tendencies of respondents with different MBTI personality types and adds style description prompts to assist in image generation. The study finds that this method can better predict the interior design styles favored by certain MBTI personality types. This research contributes to addressing aesthetic biases between designers and homeowners, bringing innovative ideas and methods to interior design, and is expected to enhance homeowners’ satisfaction.