bluuebunny/crossref_metadata_2025_split huggingface dataset:
Glycemic control and cancer outcomes in oncologic patients with diabetes: an Italian Association of Medical Oncology (AIOM), Italian Association of Medical Diabetologists (AMD), Italian Society of Diabetology (SID), Italian Society of Endocrinology (SIE), Italian Society of Pharmacology (SIF) multidisciplinary critical view
Authors: Natalicchio A. , Marrano N. , Montagnani M. , Gallo M. , Faggiano A. , Zatelli MC , Argentiero A. , Del Re M. , D’Oronzo S. , Fogli S. , Franchina T. , Giuffrida D. , Gori S. , Ragni A. , Marino G. , Mazzilli R. , Monami M. , Morviducci L. , Renzelli V. , Russo A. , Sciacca L. , Tuveri E. , Cortellini A. , Di Maio M. , Candido R. , Perrone F. , Aimaretti G. , Avogaro A. , Silvestris N. , Giorgino F. 
Published: June 2024

AbstractBackground: Increasing evidence suggests that diabetes increases the risk of developing different types of cancer. Hyperinsulinemia, hyperglycemia and chronic inflammation, characteristic of diabetes, could represent possible mechanisms involved in cancer development in diabetic patients. At the same time, cancer increases the risk of developing new-onset diabetes, mainly caused by the use of specific anticancer therapies. Of note, diabetes has been associated with a ∼10% increase in mortality for all cancers in comparison with subjects who did not have diabetes. Diabetes is associated with a worse prognosis in patients with cancer, and more recent findings suggest a key role for poor glycemic control in this regard. Nevertheless, the association between glycemic control and cancer outcomes in oncologic patients with diabetes remains unsettled and poorly debated. Purpose: The current review seeks to summarize the available evidence on the effect of glycemic control on cancer outcomes, as well as on the possibility that timely treatment of hyperglycemia and improved glycemic control in patients with cancer and diabetes may favorably affect cancer outcomes.
Enhancing watershed management in developing countries: insights from Ethiopia
Authors: Naji Temesgen Argaw , Teka Meskerem Abi , Alemu Esubalew Abate 
Published: June 2024

AbstractNatural resource degradation poses a major challenge to the sustainable livelihoods of farmers in developing countries, hindering progress toward achieving sustainable rural development. Watershed development and management practices (WDMPs) are powerful tools for enhancing sustainable rural development in developing countries. These practices have been shown to significantly improve livelihoods and food security. This research examined how WDM programs help achieve sustainable development in rural areas, focusing on examples from Ethiopia. This study used a systematic literature review (SLR) approach following a PRISMA review protocol. The research question was formulated using the CIMO (context, intervention, mechanisms, and outcomes) approach: “Does the watershed development and management (WDM) initiative lead to sustainable rural livelihoods?” Considering this research question, the findings indicated that WDM contributes to the socioeconomic and environmental sustainability of rural communities. It does this by enhancing households’ livelihood in terms of income generation, employment opportunities, agricultural productivity, and improvements in social services and infrastructure, as evidenced by numerous studies, thereby leading to better livelihoods and food security. This research also emphasizes the importance of community participation and supportive policies and legal frameworks for successful WDM. Overall, the systematic literature review highlights the potential of WDMPs in promoting sustainable rural development in developing countries such as Ethiopia while also highlighting the need for a supportive policy and institutional environment.
Multivariate Bayesian Time-Series Model with Multi-temporal Convolution Network for Forecasting Stock Market During COVID-19 Pandemic
Authors: Ray Paramita , Ganguli Bhaswati , Chakrabarti Amlan 
Published: June 2024

AbstractThe paper proposes a hybrid algorithm for forecasting multiple correlated time-series data, which consists of two main steps. First, it employs a multivariate Bayesian structural time series (MBSTS) approach as a base step. This method allows for the incorporation of potentially high-dimensional regression components, and it utilizes spike and slab priors to identify a parsimonious model. Second, the algorithm includes a post-model fitting diagnostic step where the residuals from the MBSTS step are processed through a multi-input/output temporal convolutional network (M-TCN) with multiple time scale feature learning. This step serves as an alternative to traditional subjective residual-based diagnostic procedures in time-series analysis, with the aim of improving forecasting accuracy. The key advantage of the M-TCN is its ability to capture sequential information efficiently. The M-TCN expands the field of convolution kernel without increasing the number of parameters, thus enhancing the capacity of model to capture complex sequential patterns. The paper presents two applications showcasing the effectiveness of the proposed hybrid algorithm. First, it utilizes pre-lockdown data from eleven Nifty stock sectoral indices to predict stock price movements, including the initial post-lockdown upturn. In the second application, it focuses on stock market data from pharmaceutical companies involved in manufacturing COVID-19 vaccines. In both cases, sentiment data sourced from newspapers and social media serve as the regression component. Through rigorous analysis, the paper demonstrates that the hybrid model outperforms various benchmark models, including LSTM, Bidirectional Encoder Representations from Transformers (BERT)-based LSTM, Deep Transformer Model, and GRU, among others, in terms of forecasting accuracy. This underscores the utility of the hybrid algorithm, particularly in predicting stock market trends during the COVID-19 pandemic period and its associated market dynamics.
Two assessors for the ordinary examination ought to result in stricter requirements for justifying appeals
Authors: Abrahamsen Eirik Bjorheim , Moen Vegard , Selvik Jon Tømmerås 
Published: June 2024

AbstractAll students at Norwegian universities and colleges have the right to complain about ordinary grading decisions. When an appeal is made, two new examiners are appointed, at least one of whom should be external. The handling of appeals in the current system is to be blind, meaning that the examiners handling the complaint should not be aware of the original grade. It also means that they are not to receive information regarding the examiners’ reasoning for the original grade or the student’s reasoning for the complaint. In this article, we discuss whether the current appeal grading system with blind grading is appropriate when ordinary appeal grading is conducted by two examiners. We argue that the students' legal rights are not in conflict with the principle that good decision-making processes should be well-informed before decisions are made. We conclude that, in cases where two assessors are used for the ordinary examination, we ought to abolish the blind aspect in the current appeal grading system.
Recycling potential of medical plastic waste
Authors: Apevienyeku Holali Kwami , Ampofo Joshua , Amankwaa Amoako James 
Published: June 2024

AbstractMedical plastic waste threatens the environment and human health if not properly handled and disposed of. This study used field visits, multi-criteria decision analysis, material testing, and data analysis to assess the feasibility of recycling medical plastic waste. The study identified medical plastic products (syringes, intravenous bags, and infusion sets) with high recyclability potential and proposed targeted recommendations for improving waste management practices. Medical plastic waste generation rates in kg/bed/day were 0.486 and 0.428. 55 kg/day and 5 kg/day of recyclable medical plastic waste are generated at KATH and KNUST hospitals, respectively. The contextual relevance of this research extends beyond the Ghanaian healthcare system, with implications for waste management practices in low and middle-income countries by contributing to the advancement of sustainable waste management practices.
Effect of elevated temperature on the mechanical properties of geopolymer concrete: a critical review
Authors: Rihan Mohammed Ali M. , Onchiri Richard Ocharo , Gathimba Naftary , Sabuni Bernadette 
Published: June 2024

AbstractThe need for concrete is increasing exponentially due to the growing population and fast urbanization. The primary constituent in concrete is ordinary Portland cement (OPC). Producing cement involves a significant quantity of embodied energy and leads to the release of greenhouse gases. Geopolymer concrete (GPC) was created to address the adverse environmental effects of carbon dioxide emissions (CO2) and the overdependence on fossil fuels in cement production. In addition to reducing environmental consequences, geopolymer concrete shows outstanding resistance to higher temperatures compared to OPC concrete, which maintains temperatures up to 1200 °C. This review investigates the field of GPC, focusing on its ability to withstand high temperatures. It briefly reviews geopolymer concrete's mechanical properties at high temperatures. It has been observed that residual compressive strength, which is essential in high-temperature GPC studies, generally increases to 150–350 °C but decreases beyond 400 °C because of microcrack formation. Moreover, enhanced tensile strength is demonstrated up to 300 °C, with a noticeable decrease above 800 °C. This study emphasizes the potential of geopolymer concrete for improving fire protection measures in the building industry.
The key to understanding core knowledge resides in the fetus
Authors: Reid Vincent M. 
Published: June 2024

Abstract
What Babies Know outlines a compelling case for why infancy research is fundamental for conceptualizing what it is to be human. There is another period in human development that is relatively inaccessible, yet is more important. In order to truly understand the nature of core knowledge, perception, and cognition, we must start not with the infant, but with the fetus.
More than language is needed to represent and combine different core knowledge components
Authors: Krøjgaard Peter , Sonne Trine , Kingo Osman S. 
Published: June 2024

Abstract
We question Spelke's key claim that the medium, in which contents from different core knowledge systems can be represented and combined, is language-based. Recalling an episodic memory, playing chess, and conducting mental rotation are tasks where core knowledge information is represented and combined. Although these tasks can be described by means of language, these tasks are not inherently language-based. Hence, language may be an important subset of an abstraction medium – not the medium as such.
Down the drain: reconstructing social practice from the content of two sewers in a Late Antique bathhouse in Jerash, Jordan
Authors: Blanke Louise , Bangsgaard Pernille , McPhillips Stephen , Pappalardo Raffaella , Penn Tim 
Published: June 2024

AbstractThis contribution examines social practices in the Central Bathhouse in Jerash in Late Antiquity based on the ceramic assemblage, vessel glass, faunal remains, and small finds retrieved from two sections of the bathhouse's sewer. We argue that although the bathhouse underwent significant architectural alterations from its construction in the 4th c. CE to its abandonment in the late 7th, the activities taking place inside the building remained largely the same. Our study shows that even towards the end of the bathhouse's lifespan, bodily grooming remained integral to the bathing experience, while food and drink were consumed on the premises even though the bathing facilities had been reduced to a bare minimum. The faunal remains indicate the type of food consumed, while the small finds illustrate a lively environment where gaming and gambling took place in a social space frequented by men, women, and children.
Poroelastic Response to Karst Conduit Pressurization: A Finite Element Modeling Exercise Toward the Use of Tiltmeters in Karst Aquifer Monitoring Applications
Authors: Gochenour Jacob Alexander , Rinehart Alex J. , Luhmann Andrew J. , Grapenthin Ronni , Bilek Susan L. 
Published: June 2024

AbstractTiltmeters have the potential to resolve ground deformation due to changes in hydraulic head induced by conduit pressurization. Conduit pressure variations cause groundwater to be stored or released from storage within the surrounding rock matrix. We modeled this process and infer whether the resulting deformation is measurable with tiltmeters and what behavior to expect by fully coupling porous media flow and solid mechanics in a poroelastic, 2D finite element model. Parameter sets globally representative of Paleozoic, Mesozoic, and Cenozoic confined and unconfined aquifers are considered. Our analysis focuses on the impact of the parameterization on pore pressure, vertical displacement, and tilt. We find that the spatial distribution of the poroelastic signal depends on the hydraulic diffusivity, and its magnitude depends on the mechanical and coupling parameters. Additional analysis of the impacts of conduit radius and depth suggests that tilt polarity could be an indicator of conduit location and relative conduit size. We calibrated the model to data observations acquired at the Santa Fe River Sink‐Rise system in north‐central Florida, US. We find that an overlying clay‐rich layer may act to partially confine the aquifer. Although the observed tilt signal is present in radial and transverse components and polarity reversals occur, we were able to recover the magnitude and general trend of the tilt response.
A Comparative Study on Wind Profiles and Surface Aerodynamic Parameters of Typhoons Over Coastland and Coastal Sea
Authors: Tang Shengming , Wang Kai , Yu Hui , Li Tiantian , Tang Jie 
Published: June 2024

AbstractUnderstanding the aerodynamic characteristics of landfalling typhoons is of great importance for both wind engineering and meteorology. This study comparatively investigated the near‐surface wind profiles and aerodynamic parameters over coastland and coastal sea areas using typhoon observational data collected by Doppler wind lidars and wind tower anemometers during the passage of 15 typhoons that made landfall over China during 2009–2020. Specifically, the three surface aerodynamic parameters of roughness length, friction velocity, and drag coefficient (Cd) were obtained using the logarithmic law wind profile method. Results showed that the near‐surface wind profiles became much closer to the power law wind profile with increase in wind speed. The values of roughness length and friction velocity over the coastal sea were found to exceed those over coastland areas when the 10‐m wind speed (U(10)) was larger than 18 m s−1. The critical wind speed at which Cd peaks over the coastal sea was found to be 24 m s−1. There are two peaks in the variation of Cd with U(10) under the condition of onshore wind over the sea, which has never been reported in previous observational studies. Finally, a formula for Cd was proposed to describe the variation in Cd with U(10) under the condition of onshore wind over land, which is expected to be applied in the typhoon surface layer scheme to improve numerical simulation of landfalling typhoons.
Explaining the Mechanism of Multiscale Groundwater Drought Events: A New Perspective From Interpretable Deep Learning Model
Authors: Cai Hejiang , Shi Haiyun , Zhou Zhaoqiang , Liu Suning , Babovic Vladan 
Published: June 2024

AbstractThis study presents a new approach to understand the causes of groundwater drought events with interpretable deep learning (DL) models. As prerequisites, accurate long short‐term memory (LSTM) models for simulating groundwater are built for 16 regions representing three types of spatial scales in the southeastern United States, and standardized groundwater index is applied to identify 233 groundwater drought events. Two interpretation methods, expected gradients (EG) and additive decomposition (AD), are adopted to decipher the DL‐captured patterns and inner workings of LSTM networks. The EG results show that: (a) temperature‐related features were the primary drivers of large‐scale groundwater droughts, with their importance increasing from 56.1% to 63.1% as the drought events approached from 6 months to 15 days. Conversely, precipitation‐related features were found to be the dominant factors in the formation of groundwater drought in small‐scale catchments, with the overall importance ranging from 59.8% to 53.3%; (b) Seasonal variations in the importance of temperature‐related factors are inversely related between large and small spatial scales, being more significant in summer for larger regions and in winter for catchments; and (c) temperature‐related factors exhibited an overall “trigger effect” on causing groundwater drought events in the studying areas. The AD method unveiled how the LSTM network behaved differently in retaining and discarding information when emulating different groundwater droughts. In summary, this study provides a new perspective for the causes of groundwater drought events and highlights the potential and prospect of interpretable DL in enhancing our understanding of hydrological processes.
Integrated Geophysical‐Petrological 3D‐Modeling of the West and Central African Rift System and Its Adjoining Areas
Authors: Fosso Téguia M Estelle Eric , Ebbing Jörg , Haas Peter , Szwillus Wolfgang 
Published: June 2024

AbstractThis study addresses the lithospheric structure of the West and Central African rift system (WCARS) and explores its origin and development in relation to the enigmatic Cameroon volcanic line (CVL). Based on a recent seismic tomography model, we subdivide the areas in tectonic domains. We perform integrated 3D geophysical and petrological forward modeling. By exploring the thickness and composition of different domains, we compare the model response to the observed topography and gravity anomalies, under consideration of the available seismic Moho depth points. Our model reveals three distinct domains within the study area: The WCARS is predominantly underlain by a Phanerozoic‐type lithospheric mantle, surrounded by the West African and the Congo Cratons, where the lithospheric mantle has a Proterozoic‐type signature. Between these domains, we identify a transition area where lithospheric thickness changes rapidly. Our preferred model shows significant variability of crustal thickness from 20 km in the rift area to 50 km beneath the cratons accompanied by thin lithosphere of 80 km in the rift area to thick lithosphere of up to 240 km beneath the cratons. The final model confirms that the WCARS' origin is passive, and suggests that the origin of the CVL, particularly its continental part, is the result of two tectonic events: (a) V‐shaped opening of the lithospheric mantle beneath the WCARS, resulting in (b) a strong variation of the lithosphere thickness at the transition between the rift zone and the northwestern part of the Congo craton.
Predicting Shoreline Changes Along the California Coast Using Deep Learning Applied to Satellite Observations
Authors: Adusumilli Susheel , Cirrito Nicholas , Engeman Laura , Fiedler Julia W. , Guza R. T. , Lange Athina M. Z. , Merrifield Mark A. , O'Reilly William , Young Adam P. 
Published: June 2024

AbstractUnderstanding and predicting changes in shoreline location are critical for coastal planners. In situ monitoring is accurate but not widely available. Satellite observations of shorelines have global coverage, but their accuracy and predictive capacity have not been fully explored. Abundant beach surveys and extensive wave observations in Southern California provide a unique ground truth for the interpretation of satellite‐derived recently wetted waterlines. We combine 23 years of waterline position estimates from satellite imagery with nearshore wave hindcasts and tides to train and test a deep neural network (DNN). The trained DNN uses only tides and waves as predictors at transects with satellite coverage and wave estimates to predict beach width and, for the first time, seasonal average beach slopes. Beach width changes hindcast using DNN have at least fair skill (>0.3) for 50% of transects, where the skill was calculated relative to the mean of extensive new in situ survey data from in San Diego County. The DNN also predicted shoreline changes to within 10 m (the nominal uncertainty in satellite‐derived shorelines) for 64% of transects lacking ground truth. DNN and survey estimates of seasonal beach slope changes also agree qualitatively.
DDX41 haploinsufficiency causes inefficient hematopoiesis under stress and cooperates with p53 mutations to cause hematologic malignancy
Authors: Stepanchick Emily , Wilson Andrew , Sulentic Analise M. , Choi Kwangmin , Hueneman Kathleen , Starczynowski Daniel T. , Chlon Timothy M. 
Published: June 2024

AbstractGermline heterozygous mutations in DDX41 predispose individuals to hematologic malignancies in adulthood. Most of these DDX41 mutations result in a truncated protein, leading to loss of protein function. To investigate the impact of these mutations on hematopoiesis, we generated mice with hematopoietic-specific knockout of one Ddx41 allele. Under normal steady-state conditions, there was minimal effect on lifelong hematopoiesis, resulting in a mild yet persistent reduction in red blood cell counts. However, stress induced by transplantation of the Ddx41+/− BM resulted in hematopoietic stem/progenitor cell (HSPC) defects and onset of hematopoietic failure upon aging. Transcriptomic analysis of HSPC subsets from the transplanted BM revealed activation of cellular stress responses, including upregulation of p53 target genes in erythroid progenitors. To understand how the loss of p53 affects the phenotype of Ddx41+/− HSPCs, we generated mice with combined Ddx41 and Trp53 heterozygous deletions. The reduction in p53 expression rescued the fitness defects in HSPC caused by Ddx41 heterozygosity. However, the combined Ddx41 and Trp53 mutant mice were prone to developing hematologic malignancies that resemble human myelodysplastic syndrome and acute myeloid leukemia. In conclusion, DDX41 heterozygosity causes dysregulation of the response to hematopoietic stress, which increases the risk of transformation with a p53 mutation.
Coronin 2B deficiency induces nucleolar stress and neuronal apoptosis
Authors: Wu Hongjiao , Yang Yujie , Yi Wanying , Qiu Yue , Ma Shuangshuang , Xu Jinying , Fan Yingying , Chen Yuewen , Chen Yu 
Published: June 2024

AbstractIn eukaryotes, the nucleolus is the critical non-membranous organelle within nuclei that is responsible for ribosomal DNA (rDNA) transcription and ribosome biogenesis. The transcription of rDNA, a rate-limiting step for ribosome biogenesis, is tightly regulated to meet the demand for global protein synthesis in response to cell physiology, especially in neurons, which undergo rapid changes in morphology and protein composition during development and synaptic plasticity. However, it is unknown how the pre-initiation complex for rDNA transcription is efficiently assembled within the nucleolus in neurons. Here, we report that the nucleolar protein, coronin 2B, regulates rDNA transcription and maintains nucleolar function through direct interaction with upstream binding factor (UBF), an activator of RNA polymerase I transcriptional machinery. We show that coronin 2B knockdown impairs the formation of the transcription initiation complex, inhibits rDNA transcription, destroys nucleolar integrity, and ultimately induces nucleolar stress. In turn, coronin 2B-mediated nucleolar stress leads to p53 stabilization and activation, eventually resulting in neuronal apoptosis. Thus, we identified that coronin 2B coordinates with UBF to regulate rDNA transcription and maintain proper nucleolar function in neurons.