bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimal time recommendation model for home appliances: HSB living lab + dishwasher study
Authors: Malakhatka Elena , Hagejärd Sofie , Mazidi Mohammadreza , Corcoran Katja , Röderer Kathrin , Wallbaum Holger 
Published: December 2024

Abstract
This study investigates the effectiveness of an Optimal Time Recommendation model (OTR) in encouraging citizens to shift the usage of their home appliances, such as dishwasher to off-peak hours. The research was conducted at the HSB Living Lab + in Gothenburg city, involving 74 participants from diverse social groups, including students, one-person households, couples, and families with kids. The study employed a mixed-methods approach, combining surveys, interviews, and data from self-reporting QR-code or iPad-based web-interface. Participants were provided with personalised recommendations generated by the OTR model, which considered factors such as energy demand, grid load, electricity pricing and level of CO2. The recommendations aimed to assist users in identifying the optimal time slots for operating their home appliances during off-peak, motivated by the lower price, lower CO2 emission or both. Results indicated a positive response from participants across all social groups. Most participants reported an increased awareness of their energy consumption patterns and a willingness to adopt delay shifting practices. However, some frictions and obstacles to adopt shifting time of the behaviour were highlighted as well. The findings from this case study contribute to the existing knowledge on flexibility and Demand-Side Management (DSM). These findings can inform home appliances producers to increase the delay start function usability, policymakers to emphasise the eco-design of the white goods, and researchers in developing effective strategies to encourage energy conservation practices on a larger scale.
A Comparison between the Methodology of the Mainstream in (Neuro-)Psychology, Holzkamp’s and Vygotsky’s Approach
Authors: Nigrini Leonard , Amici Federica , Llorente Miquel 
Published: December 2024

AbstractThe present paper treats the issue of methodological assumptions in mainstream neuropsychology and, as counter-concepts, in Vygotsky’s approach and Holzkamp’s critical psychology. The analysis identifies four main assumptions concerning the methodology of mainstream neuropsychology, which are contrasted with the positions of other approaches. The methodologies of the mainstream neuropsychology vs. Holzkamp’s and Vygotsky’s approach assume: (1) mechanistic vs. dialectical materialism; (2) formal vs. dialectical logic; (3) decomposition into elements vs. units; (4) reductionism of psychic processes to the brain vs. activity as a unity of environmental and organism-pole. Despite the vast coincidence in their main assumptions, we also discuss nuances of difference between Holzkamp’s and Vygotsky’s approaches. The former, possibly due to its reference to cultural-historical activity theory (CHAT) and its theoretical neglection of the organism-pole of psychic functions, falls short of structural considerations in its accounts on phylogenetic emergence. On the other hand, Vygotsky’s neuropsychology does not fully explore the phylogenetic emergence of basic units of functional psychic organisation. This might be due to certain implications of Vygotsky’s initial accounts, which seem to highlight cultural development to the detriment of phylogenetic one.
Grounding Causal Closure or Something Near Enough
Authors: Saad Bradford 
Published: December 2024

AbstractA causal argument for physicalism is widely held to pose a problem for dualism. This view has an unobvious presupposition, namely that the causal closure of the physical has a special sort of ground. The requisite sort of ground must distinguish the causal argument for physicalism from many defective causal arguments. On behalf of physicalists, I develop an account of the ground for the causal closure of the physical, thereby putting the causal argument for physicalism back in the business of causally problematizing dualism. One consequence of my account is that physicalists can pose a causal problem for dualism using a much weaker closure premise than is generally assumed.
Exploring sensitivity and initiative in a mother-baby dyad with Video Intervention Therapy (VIT): a case study in a high-risk population
Authors: Pérez-Burriel Marc , Herreman Christian , Montuori Eliana , Sánchez-Núñez Maria Julia , Downing George 
Published: December 2024

AbstractThis preliminary report is a single case study aiming to evaluate the feasibility of Video Intervention Therapy (VIT) in difficult scenarios involving high-risk mother-infant dyads in a housing program for homeless families. The study conducted in Clermont-Ferrand, France, used the Coding Interactive Behavior (CIB) system. Ruth Feldman's framework and Stuart et al.'s 4-EFA model was applied. Three VIT sessions showcased personalized interventions, aided by the CIB's role in observing and detailing changes. The results showed in this case that maternal insensitivity, characterized by high scores in intrusiveness, interference and directiveness, goes parallel to infant’s affective disconnection and social withdrawal. The VIT and CIB mutually reinforce the team's analysis and intervention perspectives pointing towards the feasibility of the video-intervention. The findings are discussed in relation to the design of future research and the need to include video intervention (VIT) work within the service's team of direct care professionals.
Differential Regulatory Effects of Probiotics on Bone Metabolism by the Status of Bone Health and Delivery Route
Authors: Park Chaeyeon , Park Ok-Jin , Kwon Yeongkag , Lee Jueun , Yun Cheol-Heui , Han Seung Hyun 
Published: December 2024

AbstractProbiotics are known to have favorable effects on human health. Nevertheless, probiotics are not always beneficial and can cause unintended adverse effects such as bacteremia and/or inflammation in immunocompromised patients. In the present study, we investigated the effects of probiotics on the regulation of bone metabolism under different health conditions and delivery routes. Intragastric administration of Lactiplantibacillus plantarum to ovariectomized mouse models for mimicking post-menopausal osteoporosis in humans substantially ameliorated osteoporosis by increasing bone and mineral density. In contrast, such effects did not occur in normal healthy mice under the same condition. Interestingly, however, intraperitoneal administration of L. plantarum induced bone destruction by increasing osteoclast differentiation and decreasing osteoblast differentiation. Furthermore, when L. plantarum was implanted into mouse calvarial bone, it potently augmented bone resorption. Concordantly, L. plantarum upregulated osteoclastogenesis and downregulated osteoblastogenesis in in vitro experiments. These results suggest that L. plantarum can have distinct roles in the regulation of bone metabolism depending on bone health and the delivery route.
Your visualisations are going places: SciVis on gaming consoles
Authors: Becher Michael , Müller Christoph , Sellenthin Dominik , Ertl Thomas , Reina Guido , Weiskopf Daniel 
Published: December 2024

Abstract
Gaming consoles, whether stationary or handheld, are designed to provide a reasonably high level of computing power to run contemporary video games at an attractive price point, a compact form factor and modest energy consumption. While consoles have traditionally been closed-off systems, recent versions of the Xbox allow the development of apps for the Universal Windows Platform (UWP) on retail devices, making it potentially a suitable platform for bringing scientific visualisation (SciVis) applications to the masses. We describe how to run such applications, namely volume rendering and ray casting of spherical glyphs, on commodity gaming systems, not only on the Xbox Series X/S, but also on handheld devices like the Steam Deck. We detail the challenges and limitations we encountered during the implementation and provide the results of an extensive study of rendering performance, not only proving the viability of the approach but also allowing for a cost and benefit evaluation compared to standard desktop computers.

Graphical abstract
Quantifying performance gains of DirectStorage for the visualisation of time-dependent particle datasets
Authors: Müller Christoph , Ertl Thomas 
Published: December 2024

Abstract
Visualisation is an essential tool for analysing unstructured particle data as they are produced, for instance, in molecular dynamics or astrodynamics simulations. Such simulations often comprise multiple time steps, and scientists produce datasets with more and more particles in each step. To handle the steadily increasing size of these simulations, many solutions based on organising the data efficiently or reducing their amount using compression have been proposed over the years. Recently, a new storage API called DirectStorage has been introduced on Xbox consoles and Windows. DirectStorage promises a dramatic reduction of loading times in games by making the transfer from NVMe drives to graphics memory more efficient. That begs the question of whether DirectStorage is also beneficial for visualising time-dependent particle data that have to be streamed from disc to the GPU and whether a potential improvement in throughput enables interactive streaming of frames that traditional APIs cannot handle. For that, we implemented a benchmarking application that supports different streaming methods. We report on the results of an extensive series of tests with varying parameters that influence the streaming performance, which show that the performance of DirectStorage is highly dependent on the choice of various parameters.

Graphic Abstract
We provide an empirical evaluation for the performance gains to be expected when using the DirectStorage API for rendering dynamic particle data set like the one on the right side. For that, we compare the overlapping DirectStorage-based I/O scheme depicted on at the bottom with traditional methods
Digital light processing 3D printing of dual crosslinked meniscal scaffolds with enhanced physical and biological properties
Authors: Menon Abhay , Elkhoury Kamil , Zahraa Amer , Sapudom Jiranuwat , Rahic Zerina , Gunsalus Kristin C. , Teo Jeremy , Gupta Nikhil , Vijayavenkataraman Sanjairaj 
Published: December 2024

AbstractRegenerating damaged meniscal tissue remains a significant challenge due to the meniscus’ limited capacity for self-repair. Photocrosslinkable hydrogels, like gelatin methacryloyl (GelMA), offer a promising solution for meniscal regeneration by providing structural flexibility to accommodate the meniscus’ complex geometry while enabling the incorporation of bioactive molecules and cells. However, GelMA alone often lacks the mechanical robustness required for load-bearing applications. In this study, we introduce a dual-crosslinked GelMA scaffold, enhanced with tannic acid (TA), designed to replicate the mechanical properties of the native meniscus. By adjusting TA concentrations, we successfully fine-tuned the scaffold’s compressive modulus to match that of human meniscal tissue. This dual crosslinking not only improved mechanical strength but also resulted in a denser matrix with smaller pore sizes and reduced degradation and swelling rates. The optimized GelMA-TA formulation was 3D-printed into complex shapes, demonstrating its potential for producing patient-specific scaffolds. Beyond its mechanical benefits, the GelMA-TA scaffold exhibited excellent antioxidant and antibacterial properties. Human mesenchymal stem cells seeded onto the scaffold showed high viability, increased proliferation, and successful chondrogenic differentiation. Additionally, the GelMA-TA scaffold acted as an immunomodulatory biomaterial, suppressing pro-inflammatory responses in monocytes while promoting an anti-inflammatory, pro-regenerative M2a macrophage phenotype. These findings suggest that the GelMA-TA scaffold holds strong potential as a viable solution for meniscal tissue repair, offering both structural integrity and enhanced biological functionality.
Graphical abstract
Improving Global Reservoir Parameterizations by Incorporating Flood Storage Capacity Data and Satellite Observations
Authors: Shen Youjiang , Yamazaki Dai , Pokhrel Yadu , Zhao Gang 
Published: December 2024

AbstractAccurate reservoir representation in large‐scale river models remains challenging owing to limited access to data on reservoir operations. We contribute to model development by introducing a global machine‐learning based flood storage capacity (FSC) data set and a satellite‐based target storage reservoir operation scheme (SBTS). The FSC data set for 1,178 flood control reservoirs is constructed using multiple reservoir attributes and reported FSC data. Integrating these FSCs into SBTS enables its global applicability with generic formulations of reservoir zoning. Then, we develop SBTS by introducing monthly median values of satellite storage data as target storage parameters. With these seasonal patterns as constrains, improvements in simulation results are achieved. When simulated with observed inflow, SBTS performed significantly better (median Kling‐Gupta efficiency values of 0.52 and 0.17 for outflow and storage simulations among 289 reservoirs), compared to the previous reservoir operation scheme with linearly interpolated target storage parameter (0.41 and −0.19). Compared to two existing global schemes without seasonal target storages, SBTS demonstrates improved performance for many reservoirs whose inflow seasonal pattern is more regular. When coupled with a global river model, it improved discharge simulations across 293 downstream gauges, with overall performance, peak, and low flow improving at 40%, 21%, and 35% of gauges, respectively, compared to simulations without reservoirs. However, reservoir simulations do not improve notably due to the biases in simulated inflow to reservoirs. We demonstrated that machine‐learning FSC and satellite observations help improve reservoir parameterizations, and found that improvements in other aspects of river modeling are essential for accurately reproducing discharge patterns.
Whole-body angular momentum during stair ascent and descent in individuals with and without knee osteoarthritis
Authors: Chan Daisy O.M. , Subasinghe Arachchige Ransi S.S. , Wang Sizhong , Chan Peter P.K. , Cheung Roy T.H. 
Published: December 2024

AbstractGiven the higher fall risk and the fatal sequelae of falls on stairs, it is worthwhile to investigate the mechanism of dynamic balance control in individuals with knee osteoarthritis during stair negotiation. Whole-body angular momentum ($$\:\overrightarrow{H}$$) is widely used as a surrogate to reflect dynamic balance and failure to constrain $$\:\overrightarrow{H}$$ may increase the fall risk. This study aimed to compare the range of $$\:\overrightarrow{H}$$ between people with and without knee osteoarthritis during stair ascent and descent. Seven participants with symptomatic knee osteoarthritis and eight asymptomatic controls were instructed to ascend and descend an instrumented staircase at a fixed cadence. Kinematic and kinetic data were collected and range of $$\:\overrightarrow{H}$$ in sagittal, frontal, and transverse planes were computed. The knee osteoarthritis group exhibited greater $$\:\overrightarrow{H}$$ in the sagittal plane during both stair ascent (P = 0.005, Cohen’s d = 1.7) and descent (P = 0.020, Cohen’s d = 1.3) as well as in the transverse plane during stair descent (P = 0.015, Cohen’s d = 1.3), than the control group. These observations may be explained by greater hip flexion (P < 0.05, Cohen’s d > 1.12) and reduced knee flexion moment (P < 0.001, Cohen’s d<-2.77) during stair ascent and descent, and decreased foot progression angle (P = 0.038, Cohen’s d=-1.2) during stair descent, in individuals with knee osteoarthritis. No significant difference in frontal plane $$\:\overrightarrow{H}$$ was found between the two groups (P > 0.05). Individuals with knee osteoarthritis exhibited greater whole-body angular momentum during stair negotiation when compared to asymptomatic controls. Our findings may provide mechanistic rationale for a greater fall risk among people with knee osteoarthritis.
Cyclic quantum annealing: searching for deep low-energy states in 5000-qubit spin glass
Authors: Zhang Hao , Boothby Kelly , Kamenev Alex 
Published: December 2024

AbstractQuantum computers promise a qualitative speedup in solving a broad spectrum of practical optimization problems. The latter can be mapped onto the task of finding low-energy states of spin glasses, which is known to be exceedingly difficult. Using D-Wave’s 5000-qubit quantum processor, we demonstrate that a recently proposed iterative cyclic quantum annealing algorithm can find deep low-energy states in record time. We also find intricate structures in a low-energy landscape of spin glasses, such as a power-law distribution of connected clusters with a small surface energy. These observations offer guidance for further improvement of the optimization algorithms.
Heart rate variability parameters indicate altered autonomic tone in subjects with COVID-19
Authors: Gruionu Gabriel , Aktaruzzaman Md , Gupta Anita , Nowak Thomas V. , Ward Matthew , Everett Thomas H. 
Published: December 2024

AbstractCOVID-19 is associated with long-term cardiovascular complications. Heart Rate Variability (HRV), a measure of sympathetic (SNS) and parasympathetic (PNS) control, has been shown to predict COVID-19 outcomes and correlate with disease progression but a comprehensive analysis that includes demographic influences has been lacking. The objective of this study was to determine the balance between SNS, PNS and heart rhythm regulation in hospitalized COVID-19 patients and compare it with similar measurements in healthy volunteers and individuals with cardiovascular diseases (CVD), while also investigating the effects of age, Body Mass Index (BMI), gender and race. Lead I ECG recordings were acquired from 50 COVID-19 patients, 31 healthy volunteers, and 51 individuals with cardiovascular diseases (CVD) without COVID-19. Fourteen HRV parameters were calculated, including time-domain, frequency-domain, nonlinear, and regularity metrics. The study population included a balanced demographic profile, with 55% of participants being under 65 years of age, 54% identifying as male, and 68% identifying as White. Among the COVID-19 patients, 52% had a BMI ≥ 30 compared to 29% of healthy volunteers and 33% of CVD patients. COVID-19 and CVD patients exhibited significantly reduced time-domain HRV parameters, including SDNN and RMSSD, compared to healthy volunteers (SDNN: 0.02 ± 0.02 s vs. 0.06 ± 0.03 s, p < 0.001; RMSSD: 0.02 ± 0.02 s vs. 0.05 ± 0.03 s, p = 0.08). In the frequency domain, both COVID-19 and CVD patients showed increased low-frequency (LF) power and lower high-frequency (HF) power compared to healthy volunteers (COVID-19 LF: 18.47 ± 18.18%, HF: 13.69 ± 25.80%; Healthy LF: 23.30 ± 11.79%, HF: 22.91 ± 21.86%, p < 0.01). The LF/HF ratio was similar in COVID-19 patients (1.038 ± 1.54) and healthy volunteers (1.03 ± 0.78). Nonlinear parameters such as SD1 were significantly lower in COVID-19 patients (0.04 ± 0.04 s vs. 0.08 ± 0.05 s, p < 0.01), indicating altered autonomic regulation. Variations in HRV were observed based on demographic factors, with younger patients, females, and non-white individuals showing more pronounced autonomic dysfunction. COVID-19 patients exhibit significant alterations in HRV, indicating autonomic dysfunction, characterized by decreased vagal tone and sympathetic dominance, similar to patients with severe cardiovascular comorbidities. Despite higher heart rates, the HRV analysis suggests COVID-19 is associated with substantial disruption in autonomic regulation, particularly in patients with specific demographic risk factors.
Examining the impact of globalization and natural resources on environmental sustainability in G20 countries
Authors: Wang Caihua , Mahmood Hamid , Khalid Samia 
Published: December 2024

AbstractThe G20 countries are responsible for around 75% of the world’s greenhouse gas (GHG) emissions, including the use of natural resources. In this regard, the role of globalization in achieving environmental sustainability is a relatively new topic of concern. As a result, the present study considers how globalization and natural resources affect GHG emissions, as well as the roles that renewable energy consumption and urbanization play in the G20 countries between 1990 and 2020. Moreover, this research utilizes advanced panel data estimation methods to assess these interrelationships, like CUP-FM and CUP-BC methods. The study finds that globalization and natural resource use contribute to increased GHG emissions, with a more pronounced effect in high-income countries because most of the countries have extended carbon taxes or emissions trading systems in the last few years. Conversely, the adoption of renewable energy is associated with a reduction in emissions, underscoring the importance of transitioning to cleaner energy sources. Urbanization trends also correlate positively with GHG emissions, highlighting the environmental impact of rapid urban growth, particularly in middle-income countries. These results underscore the need for targeted policy interventions. High-income countries should intensify efforts to reduce emissions through renewable energy and stricter regulations on resource consumption. While, middle-income countries require support to manage urbanization and adopt sustainable practices. This study provides crucial insights into the complex dynamics of globalization, resource use, and sustainability, offering valuable guidance for policymakers and researchers engaged in environmental management and climate change mitigation.
Road terrain recognition based on tire noise for autonomous vehicle
Authors: Yang Dongsheng , Zhang Dongmin , Yuan Yi , Lei Zhaoyu , Ding Binlei , Bo Lei 
Published: December 2024

AbstractEffective road terrain recognition is crucial for enhancing the driving safety, passability, and comfort of autonomous vehicles. This study addresses the challenges of accurately identifying diverse road surfaces using deep learning in complex environments. We introduce a novel end-to-end Tire Noise Recognition Residual Network (TNResNet) integrated with a time-frequency attention module, designed to capture and leverage time-frequency information from tire noise signals for road terrain classification. Our method was evaluated on five distinct road types: asphalt, cement, grass, mud, and sand. The performance of TNResNet was rigorously compared against traditional machine learning techniques, including Decision Trees, K-Nearest Neighbors, and Support Vector Machines, as well as advanced deep learning models like Long Short-Term Memory and Convolutional Neural Networks. Experimental results demonstrate that TNResNet achieves superior classification accuracy of 99.48%, outperforming all comparative methods. This work not only establishes a robust framework for road terrain identification but also showcases the significant practical implications of TNResNet in the realm of autonomous vehicle navigation.