bluuebunny/crossref_metadata_2025_split huggingface dataset:
The status of pyrethroid resistance mutation frequencies in Varroa destructor populations in the most important beekeeping areas of Türkiye
Authors: Celikkol Elif , Dogac Ersin 
Published: January 2025

Abstract
The Varroa destructor (hereafter referred to as Varroa) is a major pest of honeybees that is generally controlled using pyrethroid-based acaricides. However, resistance to these insecticides has become a growing problem, driven by the acquisition of knockdown resistance (kdr) mutations in the mite’s voltage-gated sodium channel (vgsc) gene. Resistance mutations in the vgsc gene, such as the L925V mutation, can confer resistance to pyrethroids like flumethrin and tau-fluvalinate. Monitoring genotypic resistance through molecular mutation screening is crucial for tracking and mitigating resistance spread. In this study, the frequency of resistance mutations in the vgsc was examined using a Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) approach in Varroa populations sampled throughout the Mediterranean, Aegean, and Black Sea regions of Türkiye. Considering all the samples analyzed, the results demonstrated a mean resistance allele frequency of 83.29%, indicating a relatively high frequency of resistant alleles. We observed 94.58%, 85.71%, and 69.58% resistant allele frequencies in populations sampled from the Mediterranean, Aegean, and Black Sea regions, respectively, in our study. The results of our investigation demonstrated substantial regional variations in the frequencies of resistant alleles among Varroa populations throughout Türkiye, with notably elevated resistance levels observed in the Mediterranean and Aegean regions. Due to the significant resistance mutation frequency differences between both provinces and regions, long-term monitoring of resistance alleles and the planning of regional control strategies are required for effective control of this pest.
Quantum theory of the Lemaître model for gravitational collapse
Authors: Kiefer Claus , Mohaddes Hamid 
Published: January 2025

Abstract
We investigate the quantum fate of the classical singularities that occur by gravitational collapse of a dust cloud. For this purpose, we address the quantization of a model first proposed by Georges Lemaître in 1933. We find that the singularities can generically be avoided. This is a consequence of unitary evolution in the quantum theory, whereby the quantum dust cloud collapses, bounces at a minimal radius and re-expands.
Heuristics for the run-length encoded Burrows–Wheeler transform alphabet ordering problem
Authors: Major Lily , Clare Amanda , Daykin Jacqueline W. , Mora Benjamin , Zarges Christine 
Published: January 2025

Abstract
The Burrows–Wheeler Transform (BWT) is a string transformation technique widely used in areas such as bioinformatics and file compression. Many applications combine a run-length encoding (RLE) with the BWT in a way which preserves the ability to query the compressed data efficiently. However, these methods may not take full advantage of the compressibility of the BWT as they do not modify the alphabet ordering for the sorting step embedded in computing the BWT. Indeed, any such alteration of the alphabet ordering can have a considerable impact on the output of the BWT, in particular on the number of runs. For an alphabet

$$\Sigma $$

Σ

containing

$$\sigma $$

σ

characters, the space of all alphabet orderings is of size

$$\sigma !$$

σ
!

. While for small alphabets an exhaustive investigation is possible, finding the optimal ordering for larger alphabets is not feasible. Therefore, there is a need for a more informed search strategy than brute-force sampling the entire space, which motivates a new heuristic approach. In this paper, we explore the non-trivial cases for the problem of minimizing the size of a run-length encoded BWT (RLBWT) via selecting a new ordering for the alphabet. We show that random sampling of the space of alphabet orderings usually gives sub-optimal orderings for compression and that a local search strategy can provide a large improvement in relatively few steps. We also inspect a selection of initial alphabet orderings, including ASCII, letter appearance, and letter frequency. While this alphabet ordering problem is computationally hard we demonstrate gain in compressibility.
Amplitude and Phase Imaging of CW-THz Waves Using a Photomixing System with Coherent Detection
Authors: Ben-Atar Kobi , Deninger Anselm , Engelberg Jacob , Levy Uriel 
Published: January 2025

Abstract
Continuous-Wave Terahertz (CW-THz) phase and amplitude imaging provides valuable insights into the interaction between THz waves and matter, particularly in low-absorption materials. This information is also essential for enhancing CW-THz beam profiling, a critical aspect in the design of free-space THz devices. Hereby, we introduce a single-pixel THz amplitude and phase imaging technique based on frequency scanning and fringe analysis, incorporated into a straightforward experimental setup. We validate the usefulness of the proposed approach by demonstrating two representative case studies. The first is a 3-D measurement of the amplitude and phase profile of a THz wave that is transmitted through a 3-D printed metalens. The second is beam profiling of a THz beam emitted from a photomixer antenna. In both cases, our results are in excellent agreement with previous predictions and validate the usefulness of this imaging technique. As such, we believe that the demonstrated approach will provide an important tool in the quest for establishing THz as an important method for a myriad of applications, including imaging, range finding and metrology.
Design of Perlite Based Thermal Insulation Plate and Determination of its Physical, Mechanical and Thermal Properties
Authors: Davraz Metin , Koru Murat , Isildar Nuri 
Published: January 2025

Abstract
According to the current fire regulations in Turkey, the use of insulation materials such as EPS, which are commonly employed in building insulation, is limited to buildings up to 28.5 m in height. The regulations mandate the use of Class A fire-resistant thermal insulation materials in high-rise buildings. However, these materials may present challenges in terms of application and sustainability. This study aims to develop a perlite-based thermal insulation board that is Class A fire-resistant, competitive with traditional insulation materials, and possesses optimal physical, mechanical, and thermal properties. In the production of the specimens, expanded perlite, liquid sodium silicate, and silicon powder were used, and tests for apparent density, compressive-flexural strength, capillary water absorption, and thermal conductivity were conducted in accordance with EN standards. In the first stage, the produced specimens were subjected to four different activation temperatures to determine the optimal process temperature. In the second stage, the ratios of perlite, sodium silicate, and water were varied to achieve the mixture design that yielded the highest mechanical properties from the specimens. In the final stage, water-repellent admixtures were incorporated into the batches at mass ratios of 1.5 %, 3 %, 4.5 %, and 6 %. The perlite-based thermal insulation board, which offers optimal properties in the most cost-effective manner, has an apparent density of 127 kg·m−3, compressive strength of 266 kPa, flexural strength of 156 kPa, capillary water absorption value of 0.0197 kg·m−2·min−0.5, thermal conductivity of 0.0475 Wm−1·K−1, and a unit cost of 97 $ m−3. Consequently, the insulation board developed in this study presents a viable alternative to conventional insulation materials, offering Class A fire resistance.
Using Social Media to Promote Life Skills Among Adolescents: A Debate on Opportunities, Challenges, and Implications for Health and Education
Authors: Zimmermann Elizabeth , Tomczyk Samuel 
Published: January 2025

Abstract
The digitalization of society increasingly blurs boundaries between analog and digital worlds, offering opportunities such as telemedicine and global connectivity through digital platforms. However, it also presents risks, including cyberbullying, addiction potential, harmful content, misinformation, and privacy concerns from data breaches and surveillance technologies. Social media, with its global reach, amplifies both opportunities for positive engagement and the responsibility to navigate largely unregulated content. Adolescents, due to their developing critical evaluation skills and high prevalence of mental health challenges, are particularly vulnerable in this space and must navigate the risks associated with social media while simultaneously leveraging it for essential developmental tasks, such as identity formation and building social connections. To support them in this challenge, we propose adapting the traditional life skills approach to address the challenges of social media use, empowering adolescents to navigate both digital and analog environments effectively. These life skills include critical thinking, communication, and managing emotions and stress – all of which are essential for navigating social media. Despite its complexities, social media offers a unique platform for health promotion and prevention interventions due to its wide accessibility and reach. It holds significant promise for adolescent health by providing information, motivation, and social support. However, evidence-based, youth-centered prevention strategies on these platforms are still in early development and require further research to ensure effectiveness. Prevention programs integrating proven behavior change techniques, aligning with the preferences and needs of adolescents, and teaching essential life skills can empower them to navigate digital and analog challenges effectively.
A Hybrid Approach to Model Reduction of Generalized Langevin Dynamics
Authors: Colangeli Matteo , Duong Manh Hong , Muntean Adrian 
Published: January 2025

Abstract
We consider a classical model of non-equilibrium statistical mechanics accounting for non-Markovian effects, which is referred to as the Generalized Langevin Equation in the literature. We derive reduced Markovian descriptions obtained through the neglection of inertial terms and/or heat bath variables. The adopted reduction scheme relies on the framework of the Invariant Manifold method, which allows to retain the slow degrees of freedom from a multiscale dynamical system. Our approach is also rooted on the Fluctuation–Dissipation Theorem, which helps preserve the proper dissipative structure of the reduced dynamics. We highlight the appropriate time scalings introduced within our procedure, and also prove the commutativity of selected reduction paths.
Eras of Monetary and Financial Dominance: A Copernican-Type Model of Multilayered Network with Endogenous Regimes
Authors: Bordo Michael D. , Bastidon Cécile 
Published: January 2025

Abstract

Purpose: Recent theoretical advances focus on the configuration and crises of the International Monetary System (IMS) and International Financial System (IFS) rather than their regime switchings. We argue that viewing the evolution of the IMS and IFS in the past several hundred years through the lens of the Copernican heliocentric system developed over five hundred years ago is insightful. Methods: The network representations used today for the study of the IMS and IFS can be directly transposed into the langage of stellar systems. We connect literatures in economic history and the theory of complex networks with some resonant concepts from astrophysics. We trace out the evolution across regimes of the IMS and IFS in terms of network representations of the Copernican system. Results: We provide a simple, fully testable theoretical model completed by a calibration exercise that does generate the observed historical dynamics. The IMS and IFS are described by a two-layer multiplex graph whose three key features (hub, core and distances) are affected by non-linear joint regime changes linked to a technological, institutional, geopolitical and regulatory environment variable. Conclusion: We conclude with a discussion of some perspectives of the future of the international monetary and financial systems, particularly with regard to the inertia of eras of monetary and financial dominance.
Enhancing interaction quality in interdisciplinary group work: The impact of student motivation and teacher-initiated diversity climate
Authors: Li Weiwei , Coelen Robert , Otten Sabine 
Published: January 2025

Abstract
Interdisciplinary Group Work (IGW) is increasingly being adopted in higher education settings to foster interdisciplinary competencies among students. The effectiveness of IGW hinges largely on the quality of student interactions across different disciplines. Understanding how students interact in IGW, along with the role of institutions and educators in facilitating such interaction, is crucial for enhancing interdisciplinary education quality. This study responds to the need for integrated research that considers both individual and environmental factors, employing Expectancy-Value Theory to assess perceived task value and constructing the notion of perceived teacher-initiated diversity climate as an environmental factor. It specifically examines the interactive influence of perceived benefits and costs on interdisciplinary interactions within group work and examines the impacts of perceived teacher-initiated diversity climate in boosting student’s perceptions and interactions in IGW contexts. Data collected from 108 third-year undergraduate students participating in team-based interdisciplinary programs reveals that positive perceptions of diversity significantly enhance interdisciplinary interactions, while perceived costs detract from them. It also shows that the challenges of interdisciplinarity do not substantially diminish students’ willingness to learn from various disciplinary perspectives. Importantly, perceived teacher-initiated diversity climate is related to greater positive perceptions in IGW, thereby improving interdisciplinary interaction. The paper concludes with suggestions for teachers and educational institutions on optimizing interdisciplinary education.
Mit der Digital Leadership Assistance Platform (DigiLAP) digitale Führungskompetenz entwickeln
Authors: Krick Annika , Fröhlich Lene S. , Münstermann L. Franziska , Felfe Jörg 
Published: January 2025

Zusammenfassung
In diesem Artikel der Zeitschrift Gruppe. Interaktion. Organisation. wird die Führungskräfte-Onlineplattform Digital Leadership Assistance Platform (DigiLAP) vorgestellt. Dabei wird auf die wissenschaftliche Entwicklung eingegangen, der Aufbau und die wesentlichen Funktionen sowie erste Ergebnisse der wissenschaftlichen Evaluation vorgestellt. Darüber hinaus werden Nutzungsmöglichkeiten für die Personalentwicklung und Führungskräfte dargestellt und abschließend auf Weiterentwicklungspotenzial für die Zukunft eingegangen.
Effect of Multifunction Cavitation Treatment on Helical Gear Surface
Authors: Ijiri Masataka , Yoshimura Toshihiko 
Published: January 2025

Abstract
This study proposes using multifunction cavitation (MFC) to strengthen the surface of helical gears used in transmissions. In addition, because the steel used for helical gears exhibits poor corrosion resistance in water, samples plated with electroless nickel and iron tetroxide were also investigated. In addition to using samples with modified surfaces, we used samples strengthened by carburizing and nitriding. The noncoated and plated samples showed a slight increase in surface roughness and increased compressive residual stress and hardness. The plating method that did not cause red rust during the MFC treatment was iron tetroxide plating. In the samples strengthened by carburizing and nitriding, red rust did not occur on the surface after MFC treatment, the surface roughness was suppressed, and compressive residual stress and hardness increased. The results show that the MFC treatment effectively improved the fatigue properties of gear surfaces with complex shapes.
Efficient deep neural network training via decreasing precision with layer capacity
Authors: Shen Ao , Lai Zhiquan , Sun Tao , Li Shengwei , Ge Keshi , Liu Weijie , Li Dongsheng 
Published: January 2025

Abstract
Low-precision training has emerged as a practical approach, saving the cost of time, memory, and energy during deep neural networks (DNNs) training. Typically, the use of lower precision introduces quantization errors that need to be minimized to maintain model performance, often neglecting to consider the potential benefits of reducing training precision. This paper rethinks low-precision training, highlighting the potential benefits of lowering precision: (1) low precision can serve as a form of regularization in DNN training by constraining excessive variance in the model; (2) layer-wise low precision can be seen as an alternative dimension of sparsity, orthogonal to pruning, contributing to improved generalization in DNNs. Based on these analyses, we propose a simple yet powerful technique–DPC (Decreasing Precision with layer Capacity), which directly assigns different bit-widths to model layers, without the need for an exhaustive analysis of the training process or any delicate low-precision criteria. Thorough extensive experiments on five datasets and fourteen models across various applications consistently demonstrate the effectiveness of the proposed DPC technique in saving computational cost (−16.21%–−44.37%) while achieving comparable or even superior accuracy (up to +0.68%, +0.21% on average). Furthermore, we offer feature embedding visualizations and conduct further analysis with experiments to investigate the underlying mechanisms behind DPC’s effectiveness, enhancing our understanding of low-precision training. Our source code will be released upon paper acceptance.
Adaptation of Artificial Intelligence Attitude Scale (AIAS-4) into Turkish: a validity and reliability study
Authors: Köse Neslihan , Şimşek Erdi , Demir Mehmet Can 
Published: January 2025

Abstract
The integration of Artificial Intelligence (AI) into all areas of our lives has been creating substantial changes. There certainly is an ever-growing need to assess the way public attitudes towards AI have taken shape. This study aims to adapt the Artificial Intelligence Attitude Scale (AIAS-4) (Grassini, 2023) into Turkish, where there are no measures that can be used in different contexts and by different organizations to assess the overall attitude towards AI and test its validity and reliability. The scale adaptation was conducted in two phases. The study was carried out with the participation of 422 undergraduate students during the 2023–2024 academic year. To verify the construct validity of the scale, exploratory factor analysis was conducted with 221 undergraduate students. With another group of 201 undergraduate students, confirmatory factor analysis, test-retest reliability and measurement invariance tests were computed. As in the original scale, results from exploratory and confirmatory factor analyses justified the single-factor structure of the scale with four items explaining 63.03% of the total variance, and item loadings were in the range of 0.70–0.89. The model fit values were in a good fit range (CFI: 0.998, TLI: 0.993, RMSEA: 0.048). Also, the model was strictly invariant between genders. The scale demonstrated good internal consistency in two studies, with Cronbach’s alpha of 0.86 and 0.86; and McDonald’s omega of 0.87 and 0.86. The results indicated that all items had discriminative power and therefore, the Turkish version of the scale proves to be valid and reliable and thus could be used by researchers in the Turkish context.
Highly specific amyloid and tau PET ligands for ATN classification in suspected Alzheimer’s disease patients
Authors: Matsuda Hiroshi , Hanyu Haruo , Kaneko Chikako , Ogura Masato , Yamao Tensho 
Published: January 2025

Abstract

Objective
This study aims to accurately classify ATN profiles using highly specific amyloid and tau PET ligands and MRI in patients with cognitive impairment and suspected Alzheimer’s disease (AD). It also aims to explore the relationship between quantified amyloid and tau deposition and cognitive function.

Methods
Twenty-seven patients (15 women and 12 men; age range: 64–81 years) were included in this study. Amyloid and tau PET scans were performed using 18F-NAV4694 and 18F-MK6240, respectively. For each patient, amyloid and tau PET images were visually assessed and classified as either amyloid-positive or amyloid-negative, and as 18F-MK6240 Braak stage 0 (tau-negative) or Braak stages I–VI (tau-positive). Voxel-based morphometry of three-dimensional T1-weighted MRI was used to evaluate neurodegeneration. Amyloid and tau depositions were quantified using the Centiloid scale and standardized uptake value ratio (SUVR), respectively. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE).

Results
Patients were categorized into seven ATN profiles. Six patients (22%) exhibited a normal AD biomarker profile, 15 patients (56%) fell within the Alzheimer’s continuum, and 14 patients (52%) were diagnosed with AD. Additionally, six patients (22%) displayed non-AD pathological changes. Positive and negative findings of amyloid and tau PET were concordant in 24 patients (89%). Among the 14 patients diagnosed with AD, the Centiloid scale for amyloid deposition did not show a significant negative correlation with MMSE scores (r = 0.269, p = 0.451). In contrast, the SUVR for tau deposition in the neocortex exhibited a significant negative correlation (r = −0.689, p = 0.014), while tau deposition in the mesial temporal region did not show a significant correlation (r = 0.158, p = 0.763).

Conclusion
Highly specific amyloid and tau PET scans, along with MRI, can be utilized to accurately classify ATN profiles in patients with cognitive impairment and suspected AD. The discordance in amyloid and tau PET findings in three patients allowed for a more precise AD diagnosis. Furthermore, tau PET imaging provided insight into the propagation of tau deposition in the neocortex beyond the mesial temporal region, which is associated with cognitive decline.
Long-lived winter honey bees show unexpectedly high levels of flight activity compared to short-lived summer bees
Authors: Minaud Etienne , Rebaudo François , Requier Fabrice 
Published: January 2025

Abstract
In temperate regions, the overwintering success of honey bee colonies, Apis mellifera, depends on the last generations of long-lived bees emerging in autumn, known as winter bees. While the physiological qualities of winter bees and their extended lifespan are well documented, yet literature on their flight activity performance is scarce. Here we studied the flight activity of long-lived winter honey bees and compared their performance with short-lived bees. Using radio frequency identification (RFID), we automatically monitored the number of flights, the total flight duration and the lifespan of 523 honey bees that emerged over the course of a year, including short-lived bees from spring, summer and autumn, and long-lived winter bees. We found that flight activity performance of short-lived bees decreased progressively from spring to autumn for both the number of flights and the total flight duration. Furthermore, we confirm that only a fraction of the bees emerging before winter are long-lived winter bees, with a lifespan of 143.5 ± 23.5 days (mean ± SD). With an average of 37.5 ± 44.2 flights and 12.7 ± 15.5 h of flight, we found that long-lived winter bees were substantially more active than summer and autumn short-lived bees, but performed similar activity than spring short-lived bees. We also found that a small proportion of long-lived winter bees participate in the vast majority of the flight activity of the colony. Our results suggest that the extended lifespan of long-lived winter bees does not affect their flight activity performance, probably explained by their physiological qualities.