bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bifurcation structures of a two-dimensional piecewise linear discontinuous map: analysis of a cobweb model with regime-switching expectations
Authors: Gardini Laura , Radi Davide , Schmitt Noemi , Sushko Iryna , Westerhoff Frank 
Published: April 2024

AbstractWe consider the bifurcations occurring in a two-dimensional piecewise-linear discontinuous map that describes the dynamics of a cobweb model in which firms rely on a regime-switching expectation rule. In three different partitions of the phase plane, separated by two discontinuity lines, the map is defined by linear functions with the same Jacobian matrix, having two real eigenvalues, one of which is negative and one equal to 0. This leads to asymptotic dynamics that can belong to two or three critical lines. We show that when the basic fixed point is attracting, it may coexist with at most three attracting cycles. We have determined their existence regions, in the two-dimensional parameter plane, bounded by border collision bifurcation curves. At parameter values for which the basic fixed point is repelling, chaotic attractors may exist - either one that is symmetric with respect to the basic fixed point, or, if not symmetric, the symmetric one also exists. The homoclinic bifurcations of repelling cycles leading to the merging of chaotic attractors are commented by using the first return map on a suitable line. Moreover, four different kinds of homoclinic bifurcations of a saddle 2-cycle, leading to divergence of the generic trajectory, are determined.
The soft underbelly of complexity science adoption in policymaking: towards addressing frequently overlooked non-technical challenges
Authors: Nel Darren , Taeihagh Araz 
Published: April 2024

AbstractThe deepening integration of social-technical systems creates immensely complex environments, creating increasingly uncertain and unpredictable circumstances. Given this context, policymakers have been encouraged to draw on complexity science-informed approaches in policymaking to help grapple with and manage the mounting complexity of the world. For nearly eighty years, complexity-informed approaches have been promising to change how our complex systems are understood and managed, ultimately assisting in better policymaking. Despite the potential of complexity science, in practice, its use often remains limited to a few specialised domains and has not become part and parcel of the mainstream policy debate. To understand why this might be the case, we question why complexity science remains nascent and not integrated into the core of policymaking. Specifically, we ask what the non-technical challenges and barriers are preventing the adoption of complexity science into policymaking. To address this question, we conducted an extensive literature review. We collected the scattered fragments of text that discussed the non-technical challenges related to the use of complexity science in policymaking and stitched these fragments into a structured framework by synthesising our findings. Our framework consists of three thematic groupings of the non-technical challenges: (a) management, cost, and adoption challenges; (b) limited trust, communication, and acceptance; and (c) ethical barriers. For each broad challenge identified, we propose a mitigation strategy to facilitate the adoption of complexity science into policymaking. We conclude with a call for action to integrate complexity science into policymaking further.
Nicotinamide Mononucleotide and Nicotinamide Riboside Reverse Ovarian Aging in Rats Via Rebalancing Mitochondrial Fission and Fusion Mechanisms
Authors: Arslan Nazli Pinar , Taskin Mesut , Keles Osman Nuri 
Published: April 2024

Abstract
Purpose
This study examined the effects of nicotinamide mononucleotide (NMN) and nicotinamide riboside (NR) on folliculogenesis and mitochondrial dynamics (fission and fusion mechanisms) in ovaries of middle-aged female rats.

Methods
Experimental groups were young, middle-aged (control), middle-aged + NMN and middle-aged + NR. NMN was administered at a concentration of 500 mg/kg intraperitoneally but NR at a concentration of 200 mg/kg by gavage. Follicle stimulating hormone (FSH) and luteinizing hormone (LH) levels were analyzed by ELISA. Hematoxylin-eosin staining sections were used for histopathological examination and follicles-counting. Expression levels of mitochondrial fission (Drp1, Mff and Fis1) and fusion (Mfn1, Mfn2, Opa1, Fam73a and Fam73b) genes as well as Sirt1 gene were analyzed by RT-PCR. Expression levels of fission-related proteins (DRP1, MFF, FIS1 and SIRT1) were analyzed by Western Blot.

Results
Higher ovarian index, more corpus luteum and antral follicles were detected in NMN and NR groups compared to the control. NMN or NR could rebalance LH/FSH ratio. The control group was determined to possess higher expression levels of fission genes and lower expression levels of fusion genes when compared the young group. In comparison with the control group, both NMN and NR group were found to exhibit less mitochondrial fission but more mitochondrial fussion. Higher gene and protein levels for Sirt1 were measured in NMN and NR groups compared to the control group.

Conclusion
This study reveals that NMN alone or NR alone can rebalance mitochondrial dynamics by decreasing excessive fission in middle-aged rat ovaries, thus alleviating mitochondrial stress and correcting aging-induced folliculogenesis abnormalities.
The good life as the life in touch with the good
Authors: Lovett Adam , Riedener Stefan 
Published: April 2024

AbstractWhat makes your life go well for you? In this paper, we give an account of welfare. Our core idea is simple. There are impersonally good and bad things out there: things that are good or bad period, not (or not only) good or bad for someone. The life that is good for you is the life in contact with the good. We’ll understand the relevant notion of ‘contact’ here in terms of manifestation: you’re in contact with a value when it is manifest in parts of your life or parts of your life are manifest in it. So, the more the good is manifest in your life, or your life manifest in the good, the better for you. The more the bad is manifest in your life, or your life manifest in the bad, the worse for you. We’ll argue that this account is extensionally adequate: it explains the welfare value of achievements, friendships, knowledge, pleasures and virtues. Moreover, it has a number of explanatory virtues: it’s unified, elegant and explanatorily powerful. So, we’ll suggest, it’s an excellent account of welfare, and in many ways superior to its main competitors.
The presumption of realism
Authors: Franzén Nils 
Published: April 2024

AbstractWithin contemporary metaethics, it is widely held that there is a “presumption of realism” in moral thought and discourse. Anti-realist views, like error theory and expressivism, may have certain theoretical considerations speaking in their favor, but our pretheoretical stance with respect to morality clearly favors objectivist metaethical views. This article argues against this widely held view. It does so by drawing from recent discussions about so-called “subjective attitude verbs” in linguistics and philosophy of language. Unlike pretheoretically objective predicates (e.g., “is made of wood”, “is 185 cm tall”), moral predicates embed felicitously under subjective attitude verbs like the English “find”. Moreover, it is argued that the widespread notion that moral discourse bears all the marks of fact-stating discourse is rooted in a blinkered focus on examples from English. Cross-linguistic considerations suggest that subjective attitude verbs are actually the default terms by which we ascribe moral views to people. Impressions to the contrary in English have to do with some unfortunate quirks of the term “think”.
The use of ChatGPT to find similar institutions for institutional benchmarking
Authors: Bornmann Lutz , Lepori Benedetto 
Published: April 2024

AbstractIn evaluative bibliometrics and higher education studies, one is frequently confronted with the task of comparing institutions with similar institutions. In this Letter to the Editor, a simple approach is discussed which applies ChatGPT. Although the approach seems to produce promising results (tested with an example at the level of research institute and of a university), it is necessary to investigate it systematically based on a sample including many institutions before it should be applied in research evaluation. The challenge in systematic investigations is that ChatGPT provides the user with different answers on the sane request (missing reliability).
Recurrent neural network and long short-term memory models for audio copy-move forgery detection: a comprehensive study
Authors: Akdeniz Fulya , Becerikli Yaşar 
Published: April 2024

AbstractOne of the most pressing challenges in audio forgery detection—a major topic of signal analysis and digital forensics research—is detecting copy-move forgery in audio data. Because audio data are used in numerous sectors, including security, but increasingly tampered with and manipulated, studies dedicated to detecting forgery and verifying voice data have intensified in recent years. In our study, 2189 fake audio files were produced from 2189 audio recordings on the TIMIT corpus, for a total of 4378 audio files. After the 4378 files were preprocessed to detect silent and unsilent regions in the signals, a Mel-frequency-based hybrid feature data set was obtained from the 4378 files. Next, RNN and LSTM deep learning models were applied to detect audio forgery in the data set in four experimental setups—two with RNN and two with LSTM—using the AdaGrad and AdaDelta optimizer algorithms to identify the optimum solution in the unlinear systems and minimize the loss rate. When the experimental results were compared, the accuracy rate of detecting forgery in the hybrid feature data was 76.03%, and the hybrid model, in which the features are used together, demonstrated high accuracy even with small batch sizes. This article thus reports the first-ever use of RNN and LSTM deep learning models to detect audio copy-move forgery. Moreover, because the proposed method does not require adjusting threshold values, the resulting system is more robust than other systems described in the literature.
Enhancing microspore embryogenesis in diploid potato (Solanum tuberosum L. ssp. tuberosum) germplasm
Authors: Ferrie Alison M.R. , Brost Jennifer M. 
Published: April 2024

AbstractDoubled haploidy (DH) technology has been utilized in cultivated tetraploid potato (Solanum tuberosum L. ssp. tuberosum) to accelerate crop improvement; however very little work has been done with the diploid species. Experiments were undertaken to improve microspore embryogenic response in the diploid germplasm. Several factors influencing embryogenic responses were evaluated. An increase in calcium nitrate, a reduction in the plant growth regulators 6-benzyladenine (BA) and α-naphthaleneacetic acid (NAA), as well as an incubation temperature of 28 °C resulted in an increase in callus production and, in some cases, embryo-like structures. Validation of the modified protocol was conducted with both diploid and tetraploid potato germplasm with responses from both diploid and tetraploid. Monoploid and di-haploid plants were also regenerated from these microspore-derived calli.
Generation and characterization of cerebellar granule neurons specific knockout mice of Golli-MBP
Authors: Miyazaki Haruko , Nishioka Saki , Yamanaka Tomoyuki , Abe Manabu , Imamura Yukio , Miyasaka Tomohiro , Kakuda Nobuto , Oohashi Toshitaka , Shimogori Tomomi , Yamakawa Kazuhiro , Ikawa Masahito , Nukina Nobuyuki 
Published: April 2024

AbstractGolli–myelin basic proteins, encoded by the myelin basic protein gene, are widely expressed in neurons and oligodendrocytes in the central nervous system. Further, prior research has shown that Golli–myelin basic protein is necessary for myelination and neuronal maturation during central nervous system development. In this study, we established Golli–myelin basic protein-floxed mice to elucidate the cell-type-specific effects of Golli–myelin basic protein knockout through the generation of conditional knockout mice (Golli–myelin basic proteinsfl/fl; E3CreN), in which Golli–myelin basic proteins were specifically deleted in cerebellar granule neurons, where Golli–myelin basic proteins are expressed abundantly in wild-type mice. To investigate the role of Golli–myelin basic proteins in cerebellar granule neurons, we further performed histopathological analyses of these mice, with results indicating no morphological changes or degeneration of the major cellular components of the cerebellum. Furthermore, behavioral analysis showed that Golli–myelin basic proteinsfl/fl; E3CreN mice were healthy and did not display any abnormal behavior. These results suggest that the loss of Golli–myelin basic proteins in cerebellar granule neurons does not lead to cerebellar perturbations or behavioral abnormalities. This mouse model could therefore be employed to analyze the effect of Golli–myelin basic protein deletion in specific cell types of the central nervous system, such as other neuronal cells and oligodendrocytes, or in lymphocytes of the immune system.
Matching Compound Prototypes for Few-Shot Action Recognition
Authors: Huang Yifei , Yang Lijin , Chen Guo , Zhang Hongjie , Lu Feng , Sato Yoichi 
Published: April 2024

AbstractThe task of few-shot action recognition aims to recognize novel action classes using only a small number of labeled training samples. How to better describe the action in each video and how to compare the similarity between videos are two of the most critical factors in this task. Directly describing the video globally or by its individual frames cannot well represent the spatiotemporal dependencies within an action. On the other hand, naively matching the global representations of two videos is also not optimal since action can happen at different locations in a video with different speeds. In this work, we propose a novel approach that describes each video using multiple types of prototypes and then computes the video similarity with a particular matching strategy for each type of prototypes. To better model the spatiotemporal dependency, we describe the video by generating prototypes that model the multi-level spatiotemporal relations via transformers. There are a total of three types of prototypes. The first type of prototypes are trained to describe specific aspects of the action in the video e.g., the start of the action, regardless of its timestamp. These prototypes are directly matched one-to-one between two videos to compare their similarity. The second type of prototypes are the timestamp-centered prototypes that are trained to focus on specific timestamps of the video. To deal with the temporal variation of actions in a video, we apply bipartite matching to allow the matching of prototypes of different timestamps. The third type of prototypes are generated from the timestamp-centered prototypes, which regularize their temporal consistency while serving as an auxiliary summarization of the whole video. Experiments demonstrate that our proposed method achieves state-of-the-art results on multiple benchmarks.
Removal of Humic Acid from Water by Adsorption Using Chitosan and Metal Organic Framework ZIF 8 Loaded Chitosan Adsorbents
Authors: Hilmioglu Nilufer , Yumat Esra 
Published: April 2024

AbstractWater is the most necessary need for life on the earth. There are a lot of organic pollutants in water. One of the organic pollutants is natural organic substances. Humic acid, a natural organic substance, turns into very harmful substances along with other pollutants. In this study, the humic acid removal from aqueous solution by adsorption using chitosan and chitosan/ZIF 8 composite spheres was examined. Chitosan spheres cross-linked with epichlorohydrin (ECH) and composite spheres consisting of metal organic framework ZIF8 and chitosan were prepared as adsorbents. Equilibrium, kinetic, and thermodynamic studies were investigated for humic acid adsorption by pristine chitosan-ECH and composite chitosan/ZIF 8 adsorbents. Chemical adsorption was found to be compatible with the Freundlich isotherm model and the pseudo-first-order kinetic model for pure chitosan adsorbents. Studies were carried out using chitosan/ZIF8 composite adsorbent, and the most suitable models for chemical adsorption were determined as Langmuir isotherm and pseudo-second order kinetic model. The response surface method was applied with the design expert program to determine the optimum experimental conditions. The adsorption tests were carried out using chitosan-ECH, ZIF 8 and chitosan/ZIF 8 adsorbents for specified optimum conditions, and the humic acid removal was determined as 95.1%, 98.3%, and 97.3%, respectively. In addition, desorption was performed using chitosan-ECH and chitosan/ZIF 8 spheres, and the desorption efficiency was found to be 20.9% and 82.5%, respectively. It has been observed that the developed adsorbents have potential in removing humic acid from water.
Data-Driven Modeling for the Prediction of Stack Gas Concentration in a Coal-Fired Power Plant in Türkiye
Authors: Mohammadi Mandana , Saloglu Didem , Dertli Halil , Mohammadi Mitra , Ghaffari-Moghaddam Mansour 
Published: April 2024

Abstract
In this research, deep learning and machine learning methods were employed to forecast the levels of stack gas concentrations in a coal-fired power plant situated in Türkiye. Real-time data collected from continuous emission monitoring systems (CEMS) serves as the basis for the predictions. The dataset includes measurements of carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), oxygen (O2), and dust levels, along with temperatures recorded. For this analysis, deep learning methods such as multi-layer perceptron network (MLP) and long short-term memory (LSTM) models were used, while machine learning techniques included light gradient boosted machine (LightGBM) and stochastic gradient descent (SGD) models were applied. The accuracy of the models was determined by analysing their performance using mean absolute error (MAE), root means square error (RMSE), and R-squared values. Based on the results, LightGBM achieved the highest R-squared (0.85) for O2 predictions, highlighting its variance-capturing ability. LSTM excelled in NOx (R-squared 0.87) and SO2 (R-squared 0.85) prediction, while showing the top R-squared (0.67) for CO. Both LSTM and LGBM achieved R-squared values of 0.78 for dust levels, indicating strong variance explanation. Conclusively, our findings highlight LSTM as the most effective approach for stack gas concentration forecasting, closely followed by the good performance of LightGBM. The importance of these results lies in their potential to effectively manage emissions in coal-fired power plants, thereby improving both environmental and operational aspects.

Graphical Abstract
UAV-enabled software defined data collection from an adaptive WSN
Authors: Karegar Pejman A. , Al-Hamid Duaa Zuhair , Chong Peter Han Joo 
Published: April 2024

Abstract
Unmanned aerial vehicle (UAV)-based data gathering from wireless sensor networks is one of the recent research topics that has currently attracted research interest. One of the challenges for the UAV-aided WSN data collection efforts is to design an energy-efficient UAV/drone communication with arbitrarily dispersed ground sensors by improving the ground network structure. This paper aims to develop a technique titled UAV Fuzzy Travel Path' that supports UAV smooth path design and enables ground network topology shifting. A comprehensive UAV-based data collection model is proposed to enable dynamic orchestration/re-orchestration of wireless ground sensors to jointly improve network performance and UAV path fluidity. This provides a more flexible ground network framework that can be restructured based on network demands and UAV optimal paths, effectively allowing for a software-defined network concept. The main contribution of this work is the implementation of the software-defined wireless sensor network on the ground network that adaptably supports the movement of the UAV and enhances the communication network’s energy efficiency with a proposed latency analytical analysis via network orchestration/re-orchestration phases. The main significance of this research is in offering a flexible span for UAV path design than being fixed in one strict route for data gathering purposes. Four various simulation tools are employed for modelling and performance evaluation, namely MATLAB, CupCarbon, Contiki-Cooja and Mission Planner. The proposed software-defined ground network system demonstrates encouraging results in terms of network performance metrics including energy consumption of UAV versus ground sensor nodes energy usage, packet delivery rate, and the communication time of the ground orchestrated or/and re-orchestrated network.
Temperature Dependent Dynamic Response of Open-Cell Polyurethane Foams
Authors: Morrison D. , Morton J. , Foster M. , Lamberson L. 
Published: April 2024

Abstract
Background
Polyurethane foams have many uses ranging from comfort fitting seats and shoes to protective inserts in helmets and sports equipment. Current military helmet designs employ foam pads of varying densities and bulk material properties to help absorb energy from impacts ranging from quasi-static to ballistic level strain-rates.

Objective
This study aims to analyze the thermomechanical uniaxial compression behavior of a high density liner foam pad and a low density liner foam pad used in the Advanced Combat Helmet. These experiments were conducted under strain-rates of $$10^2$$

10
2

s$$^{-1}$$

-
1

and under temperature conditions ranging from -20 to 40 °C. This temperature range was chosen to simulate desert and arctic conditions, with a strain-rate regime chosen to represent loads that would occur often throughout the life of the helmet, such as drops, bumps from riding in a vehicle, or heavy collisions from falling.

Method
Multiple experimental apparatuses were used in this study, including a Shimadzu TCE-N300 thermostatic chamber (used to create the varying temperature environments) and a custom-built drop-test system (used to induce intermediate strain-rates). Every experiment was paired with two accelerometers and a high speed camera used for Digital Image Correlation (DIC) to analyze sample deformation and resultant acceleration. The foam’s mechanical response and energy absorption properties were investigated from the measured stress-strain curves. Additionally, each foam composition was analyzed with X-ray computed micro-tomography (XCT) to investigate microstructure properties pre and post-mortem.

Results
Results show that temperature decreased the energy absorption of the low density composition by 48% ± 5% as temperature changed from -20 °C to 40 °C, while energy absorption increased by 53% ± 16% for the high density composition over the same temperature.

Conclusion
A comparison between the loading response and the material’s density characteristics revealed that the foam’s mechanical properties are heavily dependent on strain-rate applications, as well as environmental factors including temperature. Several important characteristics surrounding each foam composition’s deformation mechanics and damage tolerance as a result of temperature are discussed.