bluuebunny/crossref_metadata_2025_split huggingface dataset:
Behavioural Intentions to Adopt Artificial Intelligence in Healthcare: Exploring the Perception of Healthcare Professionals
Authors: S. Swathi K. , S. Aswathy , C. Kavitha T. , Chadaga Krishnaraja , Sampathila Niranjana 
Published: January 2025

Abstract
Artificial intelligence (AI) technologies are used in healthcare to detect diseases faster, provide personalized treatment, automate some processes, and enhance hospital safety. Yet, one of the critical challenges is users’ hesitation and unwillingness to adopt technological applications in medical practice. Hence, this research aims to identify the important factors affecting professionals’ behavioural intentions to use AI in healthcare. This cross-sectional survey was conducted in Kerala, India. We proposed a framework grounded on the literature on technology acceptance theories, and the conceptual model was tested using a 20-item questionnaire with a 5-point Likert scale. The structured questionnaire was converted into a Google Form and shared with the respondents. A total of 347 respondents, including doctors, nurses, and allied healthcare professionals from 5 different private hospitals in India, participated in this study. The partial least square structural equation modelling approach was used to evaluate the proposed framework upon confirming the reliability and validity of the measurement items. The study findings reveal that perceived ease of use (PEU), perceived usefulness (PU), and facilitating conditions (FC) are the critical factors that influence the behavioural intentions (BI) of healthcare professionals to use AI. Though healthcare professionals perceived the risk of using AI, it did not affect their choice to use AI. This study gives an understanding of healthcare professionals’ behavioural intentions to use AI so that the administrators can plan and improve their strategies to implement AI in hospitals.
Spatial Mapping of Vegetation’s Potential to Counter Seasonal Groundwater Salinity in Coastal Bangladesh
Authors: Uddin Md Riaz , Uddin Ashraf , Nelson Jake , Rahman Sk Nafiz , Zahid Anwar 
Published: January 2025

Abstract
Salinity intrusion in the coastal regions of Bangladesh is particularly challenging for communities living near mangrove forests, which have salinity-dependent ecosystems. The salinity levels within groundwater aquifer systems here vary seasonally, and vegetation has the potential to serve as a mitigation strategy to reduce salinity intrusion. In this study, we focused on the southwest coastal region of Bangladesh, an area characterized by high salinity intrusion. We analyzed groundwater samples collected from monitoring wells during both dry and wet seasons. Additionally, we recorded the necessary physical and chemical parameters to support the analysis. We explored several GIS interpolation methods, including Inverse Distance Weight (IDW), Empirical Bayesian Kriging (EBK), and Kernel interpolation to map salinity while employing remote sensing techniques to map vegetation dynamics. We used spatial regression and bivariate clustering methods to identify and map the seasonal spatial dependence variation of salinity and vegetation. Our analysis indicates a negative linear relationship between salinity and vegetation dynamics, with the correlation being notably stronger in the dry season (Pearson correlation − 0.540) compared to the wet season (Pearson correlation − 0.149). The spatial regression model indicated spatial dependence between these two variables only during the dry season, with an R-squared value of 0.972. Bivariate clustering results identified approximately 20% of the area during the dry season with high average salinity and low average vegetation index values. The spatial context of this study is crucial for developing mitigation strategies for salinity intrusion, considering the vegetation dynamics of coastal regions of Bangladesh.
Magnesium phosphates experienced high-temperature transition found on the CI-like carbonaceous chondrite Yamato 980115 by Raman microspectroscopy
Authors: Yui Hiroharu , Tsychiya Hayato , Kashima Aruto , Urashima Shu-hei , Oguchi Kenichi , Imae Naoya , Yamaguchi Akira 
Published: January 2025

Abstract
Magnesium phosphate grains, minor accessory minerals found on the primitive meteorite Yamato 980115 (Y 980115), were investigated by Raman microspectroscopy. All magnesium phosphate grains found in the present study can be assigned to farringtonite, dehydrated magnesium phosphate Mg3(PO4)2-I. Since the Mg3(PO4)2-I is generally formed via the irreversible thermal transition from the polymorphs of Mg3(PO4)2–II and –III at above 750–800 degree Celsius, we can infer that the parent body of the Y 980115 meteorites experienced thermal alteration with such a high temperature. This result is in good accordance with the previous studies and the proposals on the alteration history of Y 980115 by the electron-beam microscope and X-ray diffraction analyses. Furthermore, the hydrated form of the magnesium phosphates of Mg3(PO4)2·4H2O, Mg3(PO4)2·8H2O, and Mg3(PO4)2·22H2O was not found in the present research, also suggesting that the extensive vaporization of the hydrated water molecules with magnesium phosphate occurred by such high-temperature thermal alteration. Since Y 980115 has been historically categorized to heavily aqueously altered CI (Ivuna-type) carbonaceous chondrites but has distinct characteristic to CI meteorites, the present result would provide further evidence to the complexed alteration history of the parent body of Y 980115 meteorite.

Graphical abstract
The Potential Impacts of Single-use Plastic During the COVID-19 Pandemic
Authors: Klein Kelly R. , Trumbo Jennifer , Saber Deborah , Kakkad Astha 
Published: January 2025

Abstract

Objectives
Plastics in the environment have moved from an “eye-sore” to a public health threat. Hospitals are one of the biggest users of single-use plastics, and there is growing literature looking at not only plastics in the environment but health care’s overall contribution to its growth.

Methods
This study was a retrospective review at a 411-bed level II trauma hospital over 47 months pre and post the last wave of COVID-19 affecting this hospital. Deidentified data were gathered: daily census in the emergency department, hospital census, and corresponding number of admitted COVID-19 patients. Additionally, for the same time frame, personal protective equipment (PPE) supply purchases and gross tonnage of nonhazardous refuse were obtained.

Results
There was a large increase in PPE purchased without a significant change in gross tonnage of weight of trash.

Conclusions
PPE is incredibly important to protect health care workers. However, single-use plastic is not sustainable for the environment or public health. Understanding the full effect of the pandemic on hospital waste production is critically important as health care institutions focus on strategies to decrease their carbon footprint and increase positive impacts on public health and the environment.
The European social model after the Great Recession: A recovery not genuinely inclusive
Authors: Bilbao-Ubillos Javier , Ullibarri Miren , Ochando Carlos , Intxaurburu Gurutze , Alsasua Josu 
Published: January 2025

Abstract
In spite of the upturn in the economy and in employment that has been observed in the EU since 2013 to 2019 (and after COVID-19 crisis), the gap between the figures for indicators of economic growth and those for the trends in domestic living conditions continues to be very wide; growth and newly created jobs are not resulting in a generalised improvement in the welfare of the population. This paper seeks to demonstrate that the recovery period after the Great Recession has not been one of truly inclusive recovery and to provide tentative explanations for this. We focus on the five main EU countries before Brexit. We conclude that the incidence of poverty associated with part-time work is now somewhat greater (‘in-work poverty’) and also that there has been strong containment of wages in the leading countries of the EU over the period under study, and even falls in real wages. At least, redistribution policies have shown themselves to be effective in reducing poverty.
The Realization of Portable MRI for Indigenous Communities in the USA and Canada
Authors: Birly Shana , Teeple Angela , Illes Judy 
Published: January 2025

AbstractThe paucity of existing baseline data for understanding neurologic health and the effects of injury on people from Indigenous populations is causally related to the limited representation of communities in neuroimaging research to date. In this paper, we explore ways to change this trend in the context of portable MRI, where portability has opened up imaging to communities that have been neglected or inaccessible in the past. We discuss pathways to engage local leadership, foster the participation of communities for this unprecedented opportunity, and empower field-based researchers to bring the holistic worldview embraced by Indigenous communities to neuroimaging research.
Posthumous Sperm Use in Times of War: Ethics, Law and Society
Authors: Bassan Sharon 
Published: January 2025

AbstractThis article delves into the legal developments, bioethical nuances, and societal perspectives surrounding posthumous sperm use, particularly in the context of soldiers falling during their service. It analyzes the Israeli example during The Swords of Iron War, where the bioethical dilemma is decided based on national solidarity, beyond the “clean” bioethical-legal discussion.
Payers are Morally Responsible for Reimbursing Social Care by Medical Facilities: How to Make Value-Based Payments Work for Vulnerable Patients
Authors: Riegler Jacob 
Published: January 2025

AbstractPayers have shaped the healthcare system in the United States as fee-for-service has facilitated a care model that prioritizes volume over the sake of patient care. This worsens health disparities, especially in safety net facilities where ancillary social work is both necessary clinically and completely uncompensated. Using concepts from Iris Marion Young’s Responsibility for Justice, it can be concluded that payers have a moral responsibility for reimbursing social care to address historical injustices. In this article, I describe the ethical hazards in paying for social care and propose a way to finance this through value-based payments.
It's bigger on the inside: mapping the black box of motivation
Authors: Del Giudice Marco 
Published: January 2025

Abstract
Many motivational constructs are opaque “black boxes,” and should be replaced by an explicit account of the underlying psychological mechanisms. The theory of motivational systems has begun to provide such an account. I recently contributed to this tradition with a general architecture of motivation, which connects “energization” and “direction” through the goal-setting activity of emotions, and serves as an evolutionary grounded map of motivational processes.
Mental computational processes have always been an integral part of motivation science
Authors: Richter Michael , Gendolla Guido H. E. 
Published: January 2025

Abstract
Some constructs in motivation science are certainly underdeveloped and some motivation researchers may work with underspecified constructs, as suggested by Murayama and Jach (M&J). However, this is not indicative of a general problem in motivation science. Many motivation theories focus on specific mechanisms underlying motivated behavior and thus have already adopted the computational process perspective that M&J call for.
Resurrecting the “black-box” conundrum
Authors: Alexander Patricia A. 
Published: January 2025

Abstract
In their article, Murayama and Jach contend that a mental computational model demonstrates that high-level motivations are emergent properties from underlying cognitive processes rather than instigators of behaviors. Despite points of agreement with the authors' critiques of the motivation literature, I argue that their claim of dismantling the black box of the human mind has been constructed on shaking grounds.
Needed: Clear definition and hierarchical integration of motivation constructs
Authors: Elliot Andrew J. , Sommet Nicolas 
Published: January 2025

Abstract
Murayama and Jach offer a thoughtful and timely critique of motivation constructs. We largely concur with their basic premises, but offer additional input and clarification regarding the importance of carefully considering the energization and direction components of motivation, and fully attending to the hierarchical aspect of motivation rather than prioritizing particular levels of analysis.
Connecting theories of personality dynamics and mental computational processes
Authors: Ratchford Juliette L. , Jayawickreme Eranda 
Published: January 2025

Abstract
Whole Trait Theory (and other dynamic theories of personality) can illuminate the process by which motivational states become traits. Mental computational processes constitute part of the explanatory mechanisms that drive trait manifestations. Empirical work on Whole Trait Theory may inform future research directions on mental computational processes.
The ins and outs of unpacking the black box: Understanding motivation using a multi-level approach
Authors: Wurm F. , van der Ham I. J. M. , Schomaker J. 
Published: January 2025

Abstract
Although higher-level constructs often fail to explain the mechanisms underlying motivation, we argue that purely mechanistic approaches have limitations. Lower-level neural data help us identify “biologically plausible” mechanisms, while higher-level constructs are critical to formulate measurable behavioral outcomes when constructing computational models. Therefore, we propose that a multi-level, multi-measure approach is required to fully unpack the black box of motivated behavior.
Response to the critiques (and encouragements) on our critique of motivation constructs
Authors: Murayama Kou , Jach Hayley 
Published: January 2025

Abstract
The target article argued that motivation constructs are treated as black boxes and called for work that specifies the mental computational processes underlying motivated behavior. In response to critical commentaries, we clarify our philosophical standpoint, elaborate on the meaning of mental computational processes and why past work was not sufficient, and discuss the opportunities to expand the scope of the framework.
Multi-robot movement based on a new modified source-seeking algorithm
Authors: Morsy Morsy A. , Eqab Al-Otaibi Humaid , Bin Salamah Yasser , Ahmad Irfan 
Published: January 2025

Abstract
The two main sources of difficulty for a group of mobile robots employing sensors to find a source are robot collisions and wireless ambient noise, such as light, sound, and other sounds. This paper introduces a novel approach to multi-robot system cooperation and collision avoidance: the new modified source-seeking control with noise cancelation technology. The robot team works together on an incline of a light source field; the team’s mobility is dependent upon following the upward gradient’s direction and forming a particular movement pattern. The proposed program also takes into account each robot’s size, speed limit, obstacles, and noise. The noise cancelation technique has been used to avoid the delay and false decisions to find the target point of the source. When the noise is canceled, all control inputs to the algorithm are accurate, and the feedback decision will be true. In this study, we use the MATLAB simulation tools to test the velocity, position, time delay, and performance of each robot in the used group of robots. The simulation and practical results of the robots in searching for a light source showed very satisfactory performance compared with the results in the literature.
Zero-force drag and start-up torque compensation strategies for robots
Authors: Li Chenggang , Zhu Lujin , Yang Gang , Zhang Junxian 
Published: January 2025

Abstract
A method is proposed for identifying robot gravity and friction torques based on joint currents. The minimum gravity term parameters are obtained using the Modified Denavit–Hartenberg (MDH) parameters, and the dynamic equations are linearized. The robot’s friction torque is identified using the Stribeck friction model. Additionally, a zero-force drag algorithm is designed to address the issue of excessive start-up torque during dragging. A sinusoidal compensation algorithm is proposed to perform periodic friction compensation for each stationary joint, utilizing the identified maximum static friction torque. Experimental results show that when the robot operates at a uniform low speed, the theoretical current calculated based on the identified gravity and friction fits the actual current well, with a maximum root mean square error within 50 mA, confirming the accuracy of the identification results. The start-up torque compensation algorithm reduces the robot’s start-up torque by an average of

$ 60.58\mathrm{\%}$

, improving the compliance of the dragging process and demonstrating the effectiveness of the compensation algorithm.
Naturalistic outcomes from a service evaluation of individual acceptance and commitment informed therapy for people with Type 1 and Type 2 diabetes mellitus in Croydon, South London
Authors: Ho Jason Kai Yu , Williams Kira , Knight Gemma 
Published: January 2025

Abstract
This project evaluated the outcomes of acceptance and commitment therapy (ACT)-informed interventions for individuals with Type 1 or Type 2 diabetes mellitus experiencing mental health distress related to their condition or self-management burden. A within-subjects design evaluated the effectiveness of ACT-informed interventions using pre- and post-psychological wellbeing and diabetes specific outcome measures and HbA1C data. The interventions were part of the Croydon Community Diabetes service which began in October 2020. Fifty-six service users completed psychological wellbeing outcome measures (PHQ-9, GAD-7 and CORE-10) and 38 of these service users fully completed the diabetes specific measure (either DDS or the PAID). Thirty-nine service users had HbA1C data before the start of treatment and following the end of treatment. Wilcoxon’s signed rank test was used to analyse psychological outcomes and HbA1c data. Descriptive statistics were used for diabetes specific measures due to small sample sizes. Statistically significant reductions in levels of depression, generalised anxiety, and general psychological distress were found following ACT-informed interventions. Statistically significant reductions were also observed for HbA1c readings. Although inferential statistics were not used, the data highlighted that n=21 and n=14 reported reduction in scores on the DDS and PAID, respectively. Preliminary evidence suggests that ACT-informed interventions in an NHS community diabetes clinic for a sample of people living with Type 1 or Type 2 diabetes are associated with improved psychological wellbeing and diabetes distress.

Key learning aims

(1)
To learn about the current evidence base and missing gaps in research on the use of acceptance and commitment therapy (ACT) for people living with Type 1 or Type 2 diabetes mellitus.

(2)
To provide clinicians with an example of brief individualised ACT informed psychological interventions based on a sample of people living with diabetes in South London.

(3)
To learn about the implementation of ACT informed psychological interventions in a naturalistic evaluation of a community Diabetes NHS service that reflects realistic treatment delivery.

(4)
Through the limitations discussed in this paper, we provide future suggestions for psychologists working in diabetes care for evaluating their service in a naturalistic setting. This includes the collection of data through various sources such as the use of physical health measures and therapy process measures.
Confirming the Primacy of Light Controlling Ammonium Removal in Response to Biofilm Colonization and Shade Using Experimental Streams
Authors: Vincent Anna E. S. , Tank Jennifer L. , Speir Shannon L. , Snyder Elise D. , Pruitt Abagael N. , Mahl Ursula H. , Hall Robert O. 
Published: January 2025

AbstractThe removal of riparian shading alters stream biogeochemical cycling by stimulating algal biofilms through the release of light limitation. Few studies have examined the combined effects of shading and biofilm growth on ammonium (NH4+–N) and nitrate (NO3−–N) removal in the same experiment. We quantified water column NH4+–N and NO3−–N removal using n = 176 short‐term additions in four experimental streams over 2 years and assessed the influence of shading (shaded vs. open canopy) and biofilm colonization (early vs. late) on removal using a Bayesian three‐level hierarchical model. First, we assessed the roles of biofilm and shade on NH4+–N removal. Shading lowered NH4+–N uptake velocity [Vf; slope: −0.45 (−0.69, −0.22)], while the effect of biofilm was too small to detect [0.06 (−0.18, 0.29)]. The following season, we compared NH4+–N and NO3−–N removal, and added night releases to estimate autotrophic and heterotrophic contributions to removal. Shading reduced NH4+–N and NO3−–N Vf, while the effect of biofilm often depended on shading. NH4+–N Vf was higher than NO3−–N Vf by 51% during the day and 38% at night, confirming preferential NH4+–N removal. NO3−–N Vf declined more between the Late‐Open and Late‐Shade phases compared to NH4+–N, suggesting a stronger decline in NO3−–N demand than for NH4+–N with shade during late biofilm colonization. We found no strong diel shift in NH4+–N or NO3−–N demand. Results demonstrate the primacy of light on NH4+–N and NO3−–N removal in streams. Understanding how shading and biofilm colonization alter removal is critical as streams are vulnerable to the impacts of land use change.
Rapid and Automatic UAV Detection of River Embankment Piping
Authors: Duan Quntao , Chen Baili , Luo Lihui 
Published: January 2025

AbstractWith flooding events expected to increase in both intensity and frequency in the future due to climate change, ensuring the safety of river embankments is vital to withstand flood disasters. Piping is one of the most harmful river embankment hazards in the flood season, and recent advances in unmanned aerial vehicles (UAVs) and deep learning‐based object detection have enabled efficient and automated hazard detection. In this study, a novel approach that integrates a UAV with deep learning‐based object detection and edge computing was proposed for rapid and automatic piping detection. First, a total of 104 field simulation experiments were conducted across 12 different sites in flood‐prone areas to fill gaps in the high‐quality data set, and the UAV thermal infrared and visible data sets of river embankment piping were produced, including various times (forenoon, afternoon, and night), weather conditions (clear‐sky, cloudy, and rainy), locations (bare land, paddy, grassland, and pond) and flight altitudes (10, 20, and 30 m). Second, the deep learning‐based object detection model was selected and trained on the thermal infrared and visible data sets. The well‐trained infrared and visible models have detection precisions of 92.7% and 70.4%, respectively, with recalls of 84.9% and 69.7%. Furthermore, both models exhibited great resistance to interference from several types of aquatic vegetation and could effectively detect piping on rainy days. The integration of a UAV and edge computing enabled real‐time detection of piping. The proposed method enhances hazard detection efficiency, contributing to intelligent emergency embankment management.