bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractDeep 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

AbstractRepositioning 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

AbstractLearning 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

AbstractSaintpaulia (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

AbstractThis 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

AbstractThe 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

AbstractThe 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

AbstractGlobally, 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

AbstractSynthetic 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

AbstractThe 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

Abstract
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

AbstractRemote 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.