bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of hepatic transporter function in rats using dynamic gadoxetate-enhanced MRI: a reproducibility study
Authors: Gunwhy Ebony R. , Hines Catherine D. G. , Green Claudia , Laitinen Iina , Tadimalla Sirisha , Hockings Paul D. , Schütz Gunnar , Kenna J. Gerry , Sourbron Steven , Waterton John C.
Published: August 2024

Objective

Previous studies have revealed a substantial between-centre variability in DCE-MRI biomarkers of hepatocellular function in rats. This study aims to identify the main sources of variability by comparing data measured at different centres and field strengths, at different days in the same subjects, and over the course of several months in the same centre.

Materials and methods

13 substudies were conducted across three facilities on two 4.7 T and two 7 T scanners using a 3D spoiled gradient echo acquisition. All substudies included 3–6 male Wistar-Han rats each, either scanned once with vehicle (n = 76) or twice with either vehicle (n = 19) or 10 mg/kg of rifampicin (n = 13) at follow-up. Absolute values, between-centre reproducibility, within-subject repeatability, detection limits, and effect sizes were derived for hepatocellular uptake rate (Ktrans) and biliary excretion rate (kbh). Sources of variability were identified using analysis of variance and stratification by centre, field strength, and time period.

Results

Data showed significant differences between substudies of 31% for Ktrans (p = 0.013) and 43% for kbh (p < 0.001). Within-subject differences were substantially smaller for kbh (8%) but less so for Ktrans (25%). Rifampicin-induced inhibition was safely above the detection limits, with an effect size of 75 ± 3% in Ktrans and 67 ± 8% in kbh. Most of the variability in individual data was accounted for by between-subject (Ktrans = 23.5%; kbh = 42.5%) and between-centre (Ktrans = 44.9%; kbh = 50.9%) variability, substantially more than the between-day variation (Ktrans = 0.1%; kbh = 5.6%). Significant differences in kbh were found between field strengths at the same centre, between centres at the same field strength, and between repeat experiments over 2 months apart in the same centre.

Discussion

Between-centre bias caused by factors such as hardware differences, subject preparations, and operator dependence is the main source of variability in DCE-MRI of liver function in rats, closely followed by biological between-subject differences. Future method development should focus on reducing these sources of error to minimise the sample sizes needed to detect more subtle levels of inhibition.
Multistage transfer learning for medical images
Authors: Ayana Gelan , Dese Kokeb , Abagaro Ahmed Mohammed , Jeong Kwangcheol Casey , Yoon Soon-Do , Choe Se-woon
Published: August 2024

Deep learning is revolutionizing various domains and significantly impacting medical image analysis. Despite notable progress, numerous challenges remain, necessitating the refinement of deep learning algorithms for optimal performance in medical image analysis. This paper explores the growing demand for precise and robust medical image analysis by focusing on an advanced deep learning technique, multistage transfer learning. Over the past decade, multistage transfer learning has emerged as a pivotal strategy, particularly in overcoming challenges associated with limited medical data and model generalization. However, the absence of well-compiled literature capturing this development remains a notable gap in the field. This exhaustive investigation endeavors to address this gap by providing a foundational understanding of how multistage transfer learning approaches confront the unique challenges posed by insufficient medical image datasets. The paper offers a detailed analysis of various multistage transfer learning types, architectures, methodologies, and strategies deployed in medical image analysis. Additionally, it delves into intrinsic challenges within this framework, providing a comprehensive overview of the current state while outlining potential directions for advancing methodologies in future research. This paper underscores the transformative potential of multistage transfer learning in medical image analysis, providing valuable guidance to researchers and healthcare professionals.
A dynamic model of repositioning with a Markov-switching regime
Authors: Ebina Takeshi , Nishide Katsumasa
Published: August 2024

Repositioning products and services to entice customers is a key management strategy that requires careful planning, timing, and budget allocation. This study is the first to investigate repositioning strategies by considering a Hotelling-type location model where consumer preferences change over time with short- and long-term uncertainty. This requires the firm to adjust its product positioning to continue to appeal to consumers. A key assumption is that the parameters describing the dynamics of consumer preferences are modulated by a Markov-switching regime representing long-term uncertainty. Further, this study investigates the effects of regime shift intensity on repositioning strategies. We numerically solve a simultaneous ordinary differential equation system to derive a firm’s optimal strategy, represented by repositioning thresholds that depend on the regimes. We find that in the two-regime case, one threshold is monotonic with respect to the regime shift intensity, whereas the other can be non-monotonic. This suggests that a firm should simultaneously consider the value of the current regime and option value of waiting for a regime shift, thus effectively demonstrating the significance of the uncertainty associated with regime-switching.
Evaluating the student performance prediction and action framework through a learning analytics intervention study
Authors: Alalawi Khalid , Athauda Rukshan , Chiong Raymond , Renner Ian
Published: August 2024

Learning analytics intervention (LAI) studies aim to identify at-risk students early during an academic term using predictive models and facilitate educators to provide effective interventions to improve educational outcomes. A major impediment to the uptake of LAI is the lack of access to LAI infrastructure by educators to pilot LAI, which typically requires substantial institution-wide efforts and investment to collect related data sets and develop accurate predictive models that identify at-risk students and also provide tools to facilitate interventions. This paper presents a novel LAI framework, termed Student Performance Prediction and Action (SPPA), that facilitates educators to seamlessly provide LAIs in their courses avoiding the need for large-scale institution-wide efforts and investments. Educators develop course-specific predictive models using historical course assessment data. In learning analytics, providing effective interventions is a challenge. SPPA utilises pedagogy principles in course design and interventions to facilitate effective interventions by providing insights into students’ risk levels, gaps in students’ knowledge, and personalised study/revision plans addressing knowledge gaps. SPPA was evaluated in a large undergraduate course on its ability to predict at-risk students and facilitate effective interventions as well as its ease of use by academics. The results are encouraging with high performance of predictive models, facilitating effective interventions leading to significant improved educational outcomes with positive feedback and uptake by academics. With its advantages, SPPA has the potential to catalyse and influence wide-scale adoption in LAIs.
Comprehensive expression analysis of ERF transcription factors during chilling acclimation in Saintpaulia
Authors: Kurata Daichi , Fukutomi Kento , Kubo Kanae , Shirasawa Kenta , Hirakawa Hideki , Hosokawa Munetaka
Published: August 2024

Saintpaulia (Saintpaulia ionantha), a popular indoor ornamental potted plant, is native to the highlands of Kenya and Tanzania where temperatures rarely fall below 4 °C. Chilling injury during cultivation and transportation is a major commercial problem in Saintpaulia. In this study, we investigated chilling acclimation in Saintpaulia ‘Kilauea’. Plants grown at 20 °C (14 h light/10 h dark) displayed rapid and severe chilling injury after 24-h exposure to 4 °C. However, chilling injury at 4 °C could be dramatically reduced by pre-treating the plants at 10 °C but not at 6 °C. From whole genome analysis, 161 ethylene-responsive factors (ERFs) were identified and classified into 12 clades according to existing reports. Among these ERFs, 43, 8, and 4 ERFs were upregulated at 12, 24, and 48 h after 10 °C treatment, respectively. Most of these ERFs had GCC box and/or DRE/CRT core motifs-like sequences in their upstream regions. Finally, we compared the expression of ERFs between the treatments for 24 h at 10 °C, an effective temperature for chilling acclimation, and 6 °C, an ineffective temperature. The results showed that the expression of all six ERFs we investigated was increased by the 10 °C treatment, but not or only barely increased by the 6 °C treatment. This study suggests that Saintpaulia, a subtropical plant, can acclimate to low temperatures and that ERF upregulation is involved in chilling acclimation.
MiR-146a (rs2910164) Gene Polymorphism and Its Impact on Circulating MiR-146a Levels in Patients with Inflammatory Bowel Diseases
Authors: Ghorab Rasha Ahmed , Fouad Shaimaa H. , Sherief Ahmed F. , El-Sehsah Eman M. , Shamloul Sara , Taha Sara I.
Published: August 2024

Abstract

MicroRNA-146a (miR-146a) has been involved in the pathophysiology of inflammatory bowel disease (IBD). However, the precise processes are still not entirely understood. Contradictory studies suggest that miR-146a expression could be influenced by the miR-146a rs2910164 C > G polymorphism. This case–control study aimed to investigate the association of miR-146a rs2910164 C > G gene polymorphism and its impact on circulating miR-146a expression levels in Egyptian IBD patients. We included 40 IBD patients and 30 matched healthy controls. Genotyping of miR-146a rs2910164 polymorphism and assessment of miR-146a expression level were done using quantitative real-time PCR in all participants. MiR-146a rs2910164 GG genotype and the G allele were reported in 47% and 70% of the IBD patient group, respectively. And they were associated with increased IBD risk. All the IBD patients with the CC genotype (100%) and most of those with the CG genotype (66.67%) had an inactive disease, while most IBD patients with the GG genotype (73.68%) had an active disease. The miR-146a expression level was the highest with the CC genotype and the lowest with the GG genotype. Also, miR-146a expression level decreased significantly in IBD patients than controls and with disease activity. Combined detection of fecal calprotectin with miR-146a expression level improved the diagnostic sensitivity and the negative predictive value in differentiating IBD patients with active disease from those inactive. Our study identified a strong association of miR-146a rs2910164 GG genotype and G allele with IBD-increased susceptibility and activity in the Egyptian population. The miR-146a rs2910164 polymorphism can reduce miR-146a expression levels in these patients as well. Further research on a larger sample size and different ethnic populations can be the key to progress in establishing this genetic association.
Interspecies Justice within a Normative Sustainable Development Framework–Animal-Friendly Energy Systems as a Test Case
Authors: Bossert Leonie N.
Published: August 2024

This paper argues that existing human-animal relations contribute to the pressing socio-ecological crises of our time, and therefore, they should be discussed in the context of Sustainable Development. This holds true even from a purely anthropocentric perspective, as these crises are threats to humans. However, sentient nonhuman animals possess interests as well and should be included in the moral community. Therefore, ignoring their interests in Sustainable Development is falling short. Furthermore, the paper argues that the anthropocentric perspective of Sustainable Development is flawed because the normative foundations of Sustainable Development (intra- and intergenerational justice) can be convincingly applied to nonhuman animals. According to approaches of interspecies justice, the normative foundations of Sustainable Development not merely can but should be applied to nonhuman animals. The paper argues for including nonhuman animals into the scope of justice and, therefore, in a theory of Sustainable Development. What such inclusion means at the practical level is examined in the last section of the paper, which investigates a field of application important for transforming societies into more sustainable ones, namely energy systems. This last section discusses how more sustainable, more animal-friendly energy systems would look like.
An extensive review of preparation, stabilization, and application of single and hybrid nanofluids
Authors: Das Pritam Kumar , Santra Apurba Kumar , Ganguly Ranjan , Dash Santosh Kumar , Muthusamy Suresh , Sha MizajShabil , Sadasivuni Kishor Kumar
Published: August 2024

The researchers attract nanofluids due to their improved thermal and physical properties compared to the base fluid. The colloidal mixture of nanometre-sized particles with conventional fluid is known as nanofluids. Compared with single nanofluids, hybrid nanofluids show better enhancement in thermophysical properties. Combining nanoparticles into the host fluid is called a hybrid nanofluid. The preparation of nanofluid needs more importance. However, the physiochemical properties of the nanofluid mainly depend on the stability of the nanofluid. The article aims to provide detailed information about preparing different types of single and hybrid nanofluids dispersed in various base fluids, preparation techniques, stabilization processes, applications and challenges. Different types of surfactants and characterization methods are suggested to improve the stability of the prepared solution. It was observed that all types of nanoparticles and hybrid nanoparticles could be synthesized with different base fluids with the help of the sonication process, particle-to-surfactant ratio, magnetic stirrer and many more. The two-step method is mostly preferred by the researchers compared to the single-step method to prepare the nanofluid. Application of single and hybrid nanofluids has been highlighted in different areas; few challenges have also been identified and must be checked before implementation in the industry.
Empirical modeling and sensitivity analysis of pressure rise per wavelength and frictional forces for the peristaltic flow of Bingham plastic fluids: application of response surface methodology
Authors: Rehman Amad ur , Asghar Zaheer , Zeeshan Ahmed , Marin Marin
Published: August 2024

The efficiency of mixed convection peristaltic flow can be investigated through pressure rise per wavelength $$(\Delta P_{{{\uplambda }}} )$$

(
Δ

P
λ

)

and frictional forces ($${F}_{\uplambda }$$

F
λ

). The main aim of the present study is to discover the sensitivity analysis of non-Newtonian fluids using the Bingham plastic fluid model. In order to achieve this objective, we have empirically modeled the pressure rise per wavelength $$(\Delta {P}_{\uplambda })$$

(
Δ

P
λ

)

and frictional forces ($${F}_{\uplambda }$$

F
λ

) as a function varying with leading parameters of problem. The flow problem is governed by three coupled nonlinear partial differential equations. They are reduced to nonlinear coupled ordinary differential equations by using the long wavelength and low Reynolds number approximations. They are solved numerically using MATLAB built-in routine bvp4c to analyze the sensitivity of pressure rise per wavelength ($$\Delta {P}_{\uplambda }$$

Δ

P
λ

) and frictional forces ($${F}_{\uplambda }$$

F
λ

). We first derive the empirical model among each of responses $$\Delta {P}_{\uplambda }$$

Δ

P
λ

and $${F}_{\uplambda }$$

F
λ

and physical parameters which govern the flow using response surface methodology. The goodness of fit of empirical model is decided on the basis of coefficient of determination ($${R}^{2}$$

R

2

) obtained from the analysis of variance (ANOVA). The coefficients of determination ($${R}^{2}$$

R

2

) are 99.78% both for $$\Delta {P}_{\uplambda }$$

Δ

P
λ

and$${F}_{\uplambda }$$

F
λ

. The higher values of $${R}^{2}$$

R

2

determine the goodness of fit of empirical model. No correlation has been developed to optimize $$\Delta {P}_{\uplambda }$$

Δ

P
λ

and $${F}_{\uplambda }$$

F
λ

in peristaltic flow for Bingham plastic fluids using RSM. The results of sensitivity analysis revealed that $$\Delta {P}_{\uplambda }$$

Δ

P
λ

and $${F}_{\uplambda }$$

F
λ

are most sensitive to flow rate (q) at all levels such as low (− 1), medium (0) and high (+ 1). The sensitivity of $$\Delta {P}_{\uplambda }$$

Δ

P
λ

to Bingham number (Bn) shows a distinct behavior with varying levels of flow rate (q). At low level (− 1) of flow rate (q), the sensitivity is positive, and at high level (+ 1) of flow rate (q), the sensitivity becomes negative. Conversely, the sensitivity of $${F}_{\uplambda }$$

F
λ

to Bingham number (Bn) at low to high level of flow rate (q).
Exploring the complications of climate change funding in Sub-Saharan African countries
Authors: Adom Richard Kwame , Mukoki Paul , Ngwenya Nomhle , Simatele Mulala Danny
Published: August 2024

Globally, climate change funding has become a focal point and debate among international organisations, private agencies, governments, and civil societies mainly because of its significant threats to social, economic, and the environment and the significant funds needed to adapt and mitigate its impacts. While substantial amounts of funds have been secured and distributed to governments, private organisations and institutions in the continent to mitigate and cope with the threats of climate variabilities, the outcomes have failed to meet the desired outcomes due to limited access to funding, lack of transparency in allocations and the failure of the funds to reach local communities where the impacts are significantly felt. Using a conventional approach of data collection tools predominantly of quantitative and qualitative methods and extensive literature materials, this paper explored the complexities and constraints of sourcing climate change funding and the mechanisms of distribution funds across the continent. The findings unearthed that climate funding lacks transparency and equitable distribution; furthermore, there are substantial bureaucratic processes, capacity constraints and immense conflicting priorities among countries on the continent. Our findings uncovered that addressing these anomalies will require innovative funding structures that catalyse technical assistance programmes to support the creation of new avenues for climate finance as well as reforming global financial institutions, emphasising debt reductions, freeing up additional funding for climate change mitigation and adaptation, and channelling private finance to both climate and sustainable development, particularly in the more vulnerable countries.
Monitoring and abatement of synthetic pollutants using engineered microbial systems
Authors: Maqsood Quratulain , Hussain Nazim , Sumrin Aleena , Ali Shinawar Waseem , Tariq Muhammad Rizwan , Mahnoor Muhammada
Published: August 2024

Synthetic pollutants (SPs) are a significant environmental concern due to their extensive use and persistence in the environment. Various remediation strategies have been explored to address this issue, including photocatalysis, nano-remediation, and bioremediation. Among these, bioremediation stands out as a promising approach, particularly with the use of genetically engineered (GE) microorganisms. This review focuses on the role of GE microorganisms in reducing SPs from environmental systems. GE microorganisms have been modified to enhance their ability to degrade organic and inorganic SPs efficiently. Key genes responsible for contaminant degradation have been identified and modified to improve breakdown rates. Strategies to make engineered bacteria more acceptable are also discussed. Overall, GE microorganisms represent a viable and efficient alternative to native strains for pollutant degradation, highlighting their potential in addressing environmental pollution challenges.
The folk concept of the good life: neither happiness nor well-being
Authors: Kneer Markus , Haybron Dan
Published: August 2024

The concept of a good life is usually assumed by philosophers to be equivalent to that of well-being, or perhaps of a morally good life, and hence has received little attention as a potentially distinct subject matter. In a series of experiments participants were presented with vignettes involving socially sanctioned wrongdoing toward outgroup members. Findings indicated that, for a large majority, judgments of bad character strongly reduce ascriptions of the good life, while having no impact at all on ascriptions of happiness or well-being. Taken together with earlier findings these results suggest that the lay concept of a good life is clearly distinct from those of happiness, well-being, or morality, likely encompassing both morality and well-being, and perhaps other values as well: whatever matters in a person’s life. Importantly, morality appears not to play a fundamental role in either happiness or well-being among the folk.
Phenological stages of wheat modulate effects of phosphorus fertilization in plant-soil microbial interactions
Authors: García-Díaz Celia , Siles José A. , Moreno José Luis , García Carlos , Ruiz-Navarro Antonio , Bastida Felipe
Published: August 2024

Aims

Future phosphorus (P) fertilizer availability faces challenges due to limited phosphate rock mines and strict quality regulations regarding Cd contents in phosphate rock. In this study, conventional fertilization was partially substituted with meat bone meal (MBM), sludge (S), and the organo-mineral combination of S plus MBM (SMBM), in a wheat agroecosystem.

Methods

We investigated the impact of fertilization treatments and crop phenological stages on P availability, crop yield, and soil microbial responses. Analysis included enzyme activities, microbial biomass, and the composition of bacterial and fungal communities using metabarcoding. Additionally, we estimated functional genes related to the P cycle through qPCR. Crop yield and nutrient content in plants and soil were also determined.

Results

Replacing traditional fertilization with MBM and SMBM maintained crop yield at levels equivalent to conventional fertilization. S and SMBM produced 70% and 40% (respectively) more bioavailable P compared to conventional treatment (Trad). Significant differences between treatments in soil microbial biomass were observed in the flag leaf stage. S increased in 20% total soil microbial biomass compared to Trad. Crop phenology had a stronger impact on bacterial and fungal communities than fertilization treatments. The use of S enhanced microbial biomass and activity. Yield in both MBM and SMBM plots exhibited no statistically significant differences compared to traditional fertilization.

Conclusion

Organo-mineral fertilization emerges as a sustainable strategy for maintaining crop production while improving soil functionality. Our findings emphasize the primary influence of crop phenology on shaping soil microbial communities and influencing microbial biomass and functionality.
Assessing grapevine water status in a variably irrigated vineyard with NIR/SWIR hyperspectral imaging from UAV
Authors: Laroche-Pinel E. , Vasquez K. R. , Brillante L.
Published: August 2024

Remote sensing is now a valued solution for more accurately budgeting water supply by identifying spectral and spatial information. A study was put in place in a Vitis vinifera L. cv. Cabernet-Sauvignon vineyard in the San Joaquin Valley, CA, USA, where a variable rate automated irrigation system was installed to irrigate vines with twelve different water regimes in four randomized replicates, totaling 48 experimental zones. The purpose of this experimental design was to create variability in grapevine water status, in order to produce a robust dataset for modeling purposes. Throughout the growing season, spectral data within these zones was gathered using a Near InfraRed (NIR) - Short Wavelength Infrared (SWIR) hyperspectral camera (900 to 1700 nm) mounted on an Unmanned Aircraft Vehicle (UAV). Given the high water-absorption in this spectral domain, this sensor was deployed to assess grapevine stem water potential, Ψstem, a standard reference for water status assessment in plants, from pure grapevine pixels in hyperspectral images. The Ψstem was acquired simultaneously in the field from bunch closure to harvest and modeled via machine-learning methods using the remotely sensed NIR-SWIR data as predictors in regression and classification modes (classes consisted of physiologically different water stress levels). Hyperspectral images were converted to bottom of atmosphere reflectance using standard panels on the ground and through the Quick Atmospheric Correction Method (QUAC) and the results were compared. The best models used data obtained with standard panels on the ground and allowed predicting Ψstem values with an R2 of 0.54 and an RMSE of 0.11 MPa as estimated in cross-validation, and the best classification reached an accuracy of 74%. This project aims to develop new methods for precisely monitoring and managing irrigation in vineyards while providing useful information about plant physiology response to deficit irrigation.
Large language models and linguistic intentionality
Authors: Grindrod Jumbly
Published: August 2024

Do large language models like Chat-GPT or Claude meaningfully use the words they produce? Or are they merely clever prediction machines, simulating language use by producing statistically plausible text? There have already been some initial attempts to answer this question by showing that these models meet the criteria for entering meaningful states according to metasemantic theories of mental content. In this paper, I will argue for a different approach—that we should instead consider whether language models meet the criteria given by our best metasemantic theories of linguistic content. In that vein, I will illustrate how this can be done by applying two such theories to the case of language models: Gareth Evans’ (1982) account of naming practices and Ruth Millikan’s (1984, 2004, 2005) teleosemantics. In doing so, I will argue that it is a mistake to think that the failure of LLMs to meet plausible conditions for mental intentionality thereby renders their outputs meaningless, and that a distinguishing feature of linguistic intentionality—dependency on a pre-existing linguistic system—allows for the plausible result that LLM outputs are meaningful.
Occurrence and analysis of microplastics in municipal wastewater, Poland
Authors: Ormaniec Paulina
Published: August 2024

Microplastics are a growing environmental threat and wastewater treatment plants have been identified as significant conduits for these pollutants. This study addresses microplastic loading in the influent of a large urban wastewater treatment plant, presenting a detailed analysis of their prevalence and characteristics. Our findings reveal a concentration of 4.09 microplastic particles per litre in the tributary. We performed a detailed statistical comparison of the microplastic particles, categorising them by shape, size, colour, and polymer type. Using Fourier transform total reflectance infrared spectroscopy, we identified 13 different polymer types, with polyethylene terephthalate, rubber, and polyethylene predominating. The analysis showed that textile fibres, mainly from clothing, are the most prevalent form of microplastic in wastewater, followed by fragments from the breakdown of larger plastic objects and films. This research highlights the critical need for strategic interventions to mitigate microplastic pollution at municipal sources.
Motivation in online course design using self-determination theory: an action research study in a secondary mathematics course
Authors: Shank Emily , Tang Hengtao , Morris William
Published: August 2024

With continued growth in online learning, motivation remains a key factor in persistence and achievement. Online mathematics students struggle with self-regulation and self-efficacy. As reported by Ryan and Deci (Self-determination theory: basic psychological needs in motivation, development, and wellness, Guilford Press, 2017, https://doi.org/10.3233/EFI-2004-22201), in their well-established self-determination theory, contended that satisfying the psychological needs of autonomy (involving self-regulation), competence (involving self-efficacy), and relatedness (involving a sense of belonging) creates a suitable environment for integrated extrinsic and intrinsic motivation to thrive. The purpose of this action research was to implement a self-determination theory-based online unit for mathematics students to improve their motivation levels. A convergent mixed methods action research design was employed to identify changes in the levels of autonomy, competence, and relatedness of the participants in an Algebra 2 course (n = 50) at a fully online school in the northeastern United States. Results from the motivation questionnaire and student interviews indicated a significant increase in competence and relatedness after completing the intervention. While no significant increase in autonomy was evident in the quantitative results, the qualitative findings showed some support for improved autonomy. Recommendations for online mathematics course design to support increased motivation are provided.
How to close the loop with citizen scientists to advance meaningful science
Authors: Hall Damon M. , Avellaneda-Lopez Pedro M. , Ficklin Darren L. , Knouft Jason H. , Lowry Christopher
Published: August 2024

Citizen science yields increased scientific capacity in exchange for science literacy and promises of a more responsive science to society’s needs. Yet, citizen science projects are criticized for producing few scientific outputs and having exploitative relationships with the citizens who participate. In the eagerness to capture new data, scientists can fail to see the value of citizen scientists’ expertise beyond data generation and can forget to close the loop with outputs that benefit the public interest. Citizen scientists are experts in their local environments who, when asked, can improve scientific processes and products. To the degree that citizen scientists are relegated to data collection, we shortchange opportunities to advance science. Rather than merely critique, we present an evidence-based engagement approach for listening to citizen scientist participants and incorporating their input into science processes and products that can be retrofitted onto existing citizen science projects or integrated from a project’s inception. We offer this adaptable blueprint in four steps and illustrate this approach via a crowdsourced hydrology project on the Boyne River, USA. We show how engaging voices of citizen scientists at key points in the project improves both the products of science (a real-time ecohydrological model) and the process of conducting the science (adaptations to help improve data collection). Distinct from outreach or education, considering citizen scientists as an equally interesting site of inquiry can improve the practice and outputs of science.
Subsequent fracture risk in Norwegians and immigrants with an index forearm fracture: a cohort study
Authors: Semsarian Sepideh , Omsland Tone K. , Heen Espen , Madar Ahmed Ali , Frihagen Frede , Gjertsen Jan-Erik , Solberg Lene B. , Figved Wender , Stutzer Jens-Meinhard , Borgen Tove T. , Andreasen Camilla , Hansen Ann Kristin , Bjørnerem Åshild , Dahl Cecilie
Published: August 2024

Summary

The current study investigated subsequent fracture risk following a forearm fracture in three country of birth categories: Norway, Europe and North America, and other countries. Subsequent fracture risk was modestly higher in Norwegian-born individuals compared to the two other groups. Secondary fracture prevention should be recommended regardless of country background.

Background

Fracture risk is higher in patients with a previous fracture, but whether subsequent fracture risk differs by origin of birth is unknown. This study explores subsequent fracture risk in patients with an index forearm fracture according to region of birth.

Methods

Nationwide data on forearm fractures in patients ≥ 18 years in 2008–2019 were obtained from the Norwegian Patient Registry and Statistics Norway. Index fractures were identified by ICD-10 code S52, whereas subsequent fractures included any ICD-10 fracture code. Data on country of birth were from Statistics Norway and included three regional categories: (1) Norway, (2) other Europe and North America and (3) other countries. Direct age standardization and Cox proportional hazard regression were used to analyse the data.

Results

Among 143,476 individuals with an index forearm fracture, 35,361 sustained a subsequent fracture. Norwegian-born forearm fracture patients had the highest subsequent fracture rates (516/10,000 person-years in women and 380 in men). People born outside Europe and North America had the lowest rates (278/10,000 person-years in women and 286 in men). Compared to Norwegian-born individuals, the hazard ratios (HRs) of subsequent fracture in individuals from Europe and North American were 0.93 (95% CI 0.88–0.98) in women and 0.85 (95% CI 0.79–0.92) in men. The corresponding HRs in individuals from other countries were 0.76 (95% CI 0.70–0.84) in women and 0.82 (95% CI 0.74–0.92) in men.

Conclusion

Individuals born outside Norway had a lower subsequent fracture risk than Norwegian-born individuals; however, subsequent fracture risk increased with age in all groups. Our results indicate that secondary fracture prevention should be recommended regardless of region of origin.
Effect of thinning intensity on the carbon sequestration of natural mixed coniferous and broadleaf forests in Xiaoxing’an Mountains, China
Authors: Qu Hangfeng , Dong Xibin , Liu Hui , Zhang Baoshan , Gao Tong , Meng Yuan , Ren Yunze , Zhang Ying
Published: August 2024

To study the effect of thinning intensity on the carbon sequestration by natural mixed coniferous and broadleaf forests in Xiaoxing’an Mountains, China, we established six 100 m × 100 m experimental plots in Dongfanghong Forest that varied in thinning intensity: plot A (10%), B (15%), C (20%), D (25%), E (30%), F (35%), and the control sample area (0%). A principal component analysis was performed using 50 different variables, including species diversity, soil fertility, litter characteristics, canopy structure parameters, and seedling regeneration parameters. The effects of thinning intensity on carbon sequestration were strongest in plot E (0.75), followed by D (0.63), F (0.50), C (0.48), B (0.22), A (0.11), and the control (0.06). The composite score of plot E was the highest, indicating that the carbon sequestration effect was strongest at a thinning intensity of 30%. These findings provide useful insights that could aid the management of natural mixed coniferous and broadleaf forests in Xiaoxing’an Mountains, China. This information has implications for future studies of these forests, and the methods used could aid future ecological assessments of the natural forests in Xiaoxing’an Mountains, China.
The training pathway for residents: ‘Robotic Curriculum for young Surgeons’ (RoCS) does not impair patient outcome during implementation into clinical routine
Authors: Stockheim Jessica , Andriof S. , Andric M. , Al-Madhi S. , Acciuffi S. , Franz M. , Lorenz E. , Peglow S. , Benedix F. , Perrakis A. , Croner R. S.
Published: August 2024

The “Robotic Curriculum for young Surgeons” (RoCS) was launched 03/2020 to address the increasing importance of robotics in surgical training. It aims to provide residents with foundational robotic skills by involving them early in their training. This study evaluated the impact of RoCS’ integration into clinical routine on patient outcomes. Two cohorts were compared regarding the implementation of RoCS: Cohort 1 (before RoCS) included all robot-assisted procedures between 2017 and 03/2020 (n = 174 adults) retrospectively; Cohort 2 (after RoCS) included all adults (n = 177) who underwent robotic procedures between 03/2020 and 2021 prospectively. Statistical analysis covered demographics, perioperative parameters, and follow-up data, including mortality and morbidity. Subgroup analysis for both cohorts was organ-related (upper gastrointestinal tract (UGI), colorectal (CR), hepatopancreaticobiliary system (HPB)). Sixteen procedures were excluded due to heterogeneity. In-hospital, 30-, 90-day morbidity and mortality showed no significant differences between both cohorts, including organ-related subgroups. For UGI, no significant intraoperative parameter changes were observed. Surgery duration decreased significantly in CR and HPB procedures (p = 0.018 and p < 0.001). Estimated blood loss significantly decreased for CR operations (p = 0.001). The conversion rate decreased for HPB operations (p = 0.005). Length of hospitalization decreased for CR (p = 0.015) and HPB (p = 0.006) procedures. Oncologic quality, measured by histopathologic R0-resections, showed no significant changes. RoCS can be safely integrated into clinical practice without compromising patient safety or oncologic quality. It serves as an effective training pathway to guide robotic novices through their first steps in robotic surgery, offering promising potential for skill acquisition and career advancement.
Heterogeneous empathic reactions and their associations with adherence and prosocial behaviors during a pandemic
Authors: Israelashvili Jacob , Perry Anat
Published: August 2024

The present research utilized the backdrop of the COVID-19 pandemic as a case study to explore the motives driving individuals to adhere to recommended health standards. One month into the first lockdown and eight months before the availability of vaccinations, a large sample of 1,263 individuals completed measures of empathic concern and personal distress in response to a person who contracted the virus. In addition, we measured their COVID-related behaviors, relating to benefitting another person (i.e., donation), the self (i.e., physical hygiene), or both self and other (i.e., physical distancing). Consistent with the Empathy-Altruism Hypothesis (Batson et al., 2015), we found that individuals who experience higher empathic concern, maintain greater physical distance and physical hygiene and act more generously. We further found that individuals who experienced high personal distress were less likely to act generously, albeit more likely to maintain personal hygiene and physical distance. These findings suggest that compliance with health recommendations can be encouraged by eliciting empathic concern or personal distress. Yet, compliance per se is not prosocial behavior. Any intervention aiming to increase prosocial motivation should focus on enhancing empathic concern while minimizing personal distress.
Cognitive-Inspired Deep Learning Models for Aspect-Based Sentiment Analysis: A Retrospective Overview and Bibliometric Analysis
Authors: Chen Xieling , Xie Haoran , Qin S. Joe , Chai Yaping , Tao Xiaohui , Wang Fu Lee
Published: August 2024

As cognitive-inspired computation approaches, deep neural networks or deep learning (DL) models have played important roles in allowing machines to reach human-like performances in various complex cognitive tasks such as cognitive computation and sentiment analysis. This paper offers a thorough examination of the rapidly developing topic of DL-assisted aspect-based sentiment analysis (DL-ABSA), focusing on its increasing importance and implications for practice and research advancement. Leveraging bibliometric indicators, social network analysis, and topic modeling techniques, the study investigates four research questions: publication and citation trends, scientific collaborations, major themes and topics, and prospective research directions. The analysis reveals significant growth in DL-ABSA research output and impact, with notable contributions from diverse publication sources, institutions, and countries/regions. Collaborative networks between countries/regions, particularly between the USA and China, underscore global engagement in DL-ABSA research. Major themes such as syntax and structure analysis, neural networks for sequence modeling, and specific aspects and modalities in sentiment analysis emerge from the analysis, guiding future research endeavors. The study identifies prospective avenues for practitioners, emphasizing the strategic importance of syntax analysis, neural network methodologies, and domain-specific applications. Overall, this study contributes to the understanding of DL-ABSA research dynamics, providing a roadmap for practitioners and researchers to navigate the evolving landscape and drive innovations in DL-ABSA methodologies and applications.
Anisotropy of surface morphology of carbonate rocks after reaction with acid
Authors: Yang Jian , Min Jian , Peng Junliang , Li Qin , Wang Zhouyang
Published: August 2024

In acid fracturing, acid is injected into artificial fracture to dissolve the rock, and the rock surface is shaped into the non-uniform morphology. This non-uniform morphology is the main cause of fracture conductivity after acid etching. The effects of acid type, flow rate, contact time and rock type on the non-uniform morphology of acid-etched rock surface have been studied. However, when the direction of acid flow is determined, the difference of dissolution characteristics in different directions of rock surface is not investigated. In this paper, acid rock reaction experiment and analysis of rock surface morphology after acid etching are carried out by using rock samples with flat surface. The difference of morphological characteristic parameters of rock surface in different directions under the condition of acid flow is discussed. It was found that the mean drop height, drop height range and roughness coefficient increase with the increase of acid rock reaction rate on flat rock surface. The morphological characteristic parameters of acid-etched rock face of limestone are greater than those of dolomite, which is conducive to forming acid-etched channels. According to the statistics of all experimental data, the larger average drop height of rock surface is distributed in the direction of parallel acid flow, the larger drop height range is distributed in the direction of vertical acid flow and other directions, and the larger roughness coefficient is distributed in other directions.
RecStitchNet: Learning to stitch images with rectangular boundaries
Authors: Zhang Yun , Lai Yu-Kun , Nie Lang , Zhang Fang-Lue , Xu Lin
Published: August 2024

Irregular boundaries in image stitching naturally occur due to freely moving cameras. To deal with this problem, existing methods focus on optimizing mesh warping to make boundaries regular using the traditional explicit solution. However, previous methods always depend on hand-crafted features (e.g., keypoints and line segments). Thus, failures often happen in overlapping regions without distinctive features. In this paper, we address this problem by proposing RecStitchNet, a reasonable and effective network for image stitching with rectangular boundaries. Considering that both stitching and imposing rectangularity are non-trivial tasks in the learning-based framework, we propose a three-step progressive learning based strategy, which not only simplifies this task, but gradually achieves a good balance between stitching and imposing rectangularity. In the first step, we perform initial stitching by a pre-trained state-of-the-art image stitching model, to produce initially warped stitching results without considering the boundary constraint. Then, we use a regression network with a comprehensive objective regarding mesh, perception, and shape to further encourage the stitched meshes to have rectangular boundaries with high content fidelity. Finally, we propose an unsupervised instance-wise optimization strategy to refine the stitched meshes iteratively, which can effectively improve the stitching results in terms of feature alignment, as well as boundary and structure preservation. Due to the lack of stitching datasets and the difficulty of label generation, we propose to generate a stitching dataset with rectangular stitched images as pseudo-ground-truth labels, and the performance upper bound induced from the it can be broken by our unsupervised refinement. Qualitative and quantitative results and evaluations demonstrate the advantages of our method over the state-of-the-art.
Perceptibility and Pain Thresholds in Low- and High-Frequency Alternating Current Stimulation: Implications for tACS and tTIS
Authors: Thiele Carsten , Tamm Cornelius , Ruhnau Philipp , Zaehle Tino
Published: August 2024

Transcranial electrical stimulation (tES) has emerged as a promising tool for neuromodulation, but its application is often limited by the discomfort associated with higher stimulation intensities. Newer variants like transcranial temporal interference stimulation (tTIS) utilize high-frequency alternating currents (≥ 500 Hz) to penetrate deeper brain regions while mitigating perceptual discomfort. This study sought to examine sensation and pain thresholds across various stimulation frequencies of alternating currents, aiming to explore the boundaries of comfortable intensities. Additionally, we sought to evaluate the efficacy of an anesthetizing topical cream in increasing participant comfort and potentially extending the range of tolerable stimulation levels. We recruited 37 participants and applied alternating current stimulation to the head at various frequencies (10 Hz, 20 Hz, 500 Hz, 1000 Hz, and 2000 Hz) to determine intensity-dependent perception and pain thresholds. Additionally, thresholds were determined under the influence of a topical anesthetic. Our findings confirm that as stimulation frequency increases, perceptibility decreases, with higher frequencies allowing a manyfold increase in stimulation intensity before becoming perceptible or causing pain. Additionally, the anesthetizing cream was efficacious in further reducing perceptibility and pain sensations across all frequencies. This study lays the groundwork for future research by establishing comfortable limits for stimulation intensities, particularly in the context of high-frequency stimulation. The reduced perceptibility of high-frequency stimulation, coupled with the effectiveness of anesthetizing creams, enables the administration of higher stimulation intensities for more potent neuromodulatory interventions without causing discomfort.