bluuebunny/crossref_metadata_2025_split huggingface dataset:
Who Wants to Become a Role Model? Personal Narratives of Success and Internal Dynamics of Change in Nairobi’s Ghettos
Authors: Lanne Jean-Baptiste , Pommerolle Marie-Emmanuelle 
Published: August 2024

Abstract
This article contributes to an understanding of the internal dynamics of change in Nairobi’s ghettos (Kenya). Spaces of relegation for the urban poor, referred to by our interlocutors as “ghettos”, are often portrayed either as objects of international interventionism or as deprived areas neglected by national or metropolitan policies. We argue that social and material change in these spaces can be conceptualised at the interface between personal narratives of change and the structural urban dynamics at play. Using qualitative methods of individual narratives, we examine in particular how individuals identified as successful by those around them, born and raised in Nairobi’s marginalised neighbourhoods, construct their self trajectories as role models to invest themselves as vectors of change within their “ghetto”. Drawing on literature that focuses on the power of personal and collective narratives of social change, we explore how they perform their narrative and transform it into a “narrative capital”. This way, they contribute to the production of a narrative that is partially detached from external developmentalist imperatives, emphasising the importance of intergenerational links as a driving force for change, as well as the links that the ghetto maintains with its immediate urban environment.
Reconstructing stop and nasal-initial 1st person pronouns to Proto-Trans-Himalayan
Authors: DELANCEY Scott 
Published: August 2024

Abstract
Two 1st person singular pronouns, #ŋa and #ka, are reconstructed for Proto-Trans-Himalayan. The functions of these roots and the relation between them in the proto-language have not been definitively established. Other work has presented a distinct case for a 1st person plural #ka in PTH. This paper compares the evidence for 1st person singular and plural #ka and argues that they are the same root, which in some languages has shifted from plural to singular function.
A decade of advances in black soldier fly research: from genetics to sustainability
Authors: Athanassiou C.G. , Coudron C.L. , Deruytter D. , Rumbos C.I. , Gasco L. , Gai F. , Sandrock C. , De Smet J. , Tettamanti G. , Francis A. , Petrusan J.-I. , Smetana S. 
Published: August 2024

Abstract
Black soldier fly (BSF), Hermetia illucens, is one of the most explored insect species mass-produced for feed, but also for food and technical purposes. Considering the rapid developments in both research and industrial production of this insect species in the last decade, this review intends to reflect on the most current scientific insights and define the future trends and needs for the most relevant associated research fields. The review reflects on the aspects of BSF production and reproduction, utilization of BSF biomass as components of animals’ feeds and human food. It also provides reflection on genetics, microbiology and sustainability. The analysis identifies the need in future research associated with compositions of fungal and viral communities of insects and their environments and mapping the dynamics of BSF gut physiology and microbiota in varying conditions. High interest will be devoted to establishing genomic resources, to characterize genotypic diversity, and to harness its potential through selective breeding to improve BSF performance quantitatively and/or qualitatively. Further research will follow on the use of BSF for food and feed development, potentially for specific application cases, associated with animal gut microbiome improvement and antimicrobial properties of BSF biomass. The further in-depth exploration of the potential of BSF for waste biotransformation and the assessment of its circularity potential are also expected to be major focus points of research in the next decade.
Sensitivity of the Northern Hemisphere Warming Trend to Snowpack Variability
Authors: Onuma Yukihiko , Yoshimura Kei , Nitta Tomoko , Tatebe Hiroaki , Watanabe Masahiro 
Published: August 2024

Abstract
A marked decrease in land surface snow cover within the Northern Hemisphere under global warming will warm the atmosphere near the land surface. However, minimal information exists regarding the contribution of snowpack variation to interannual surface air temperature variability. The current study investigates the effects caused by snow water equivalent (SWE) change on surface air temperature (SAT). To this end, an SWE pacemaker experiment of land–atmosphere coupling (AMIP-type) is undertaken for the period 1901–2010, during which the Model for Interdisciplinary Research on Climate, version 6 (MIROC6), atmospheric general circulation model’s SWE is continuously nudged toward SWE derived from an land-only (LMIP-type) experiment. Compared to a reference MIROC6 simulation without SWE nudging, the spatial correlation of 1980–2010 interannual SWE trends in our experiment with those in GlobSnow observation data increased by 0.31 over the Northern Hemisphere. Similarly, the linear correlation of interannual SAT with reanalysis data is greater by 0.04, 0.04, 0.08, and 0.07 for autumn, winter, spring, and summer over the region from the reference experiment, respectively. It is shown that due to this SWE nudging, the modeled interannual SAT change in the Northern Hemisphere becomes more accurate. Through a surface energy budget analysis, changes in SAT are attributed to changes in surface albedo, soil evaporation, and soil temperature. Areas of greater contribution of SWE variability to SAT variability appear to shift from south to north areas as snow melts. These results highlight surface albedo, snow hydrological, and land heat storage effects through which the SWE interannual trend on the land surface significantly controls atmospheric air temperature variability near the land surface.

Significance Statement
This study investigates the contribution of land snowpack to surface air temperature in the Northern Hemisphere using a climate model updated with observation-based estimates of snow water equivalent. A marked decrease in snowpack under global warming is expected to warm the atmosphere near the land surface. Variations in surface albedo, soil evaporation, and soil temperature through the snow–soil–atmosphere processes during the early snow-melting season are crucial for accurately simulating surface air temperature in the Northern Hemisphere. Moreover, terrestrial snowpack is a significant factor in global warming rates.
Counteracting Impacts of ENSO and the Aleutian Low on Winter Surface Air Temperature over Japan Sea Rim Region
Authors: Liu Xuefeng , Zhu Zhiwei , Takemura Kazuto , Yang Youngmin 
Published: August 2024

Abstract
Exploring the mechanisms modulating Japan Sea Rim (JSR) winter surface air temperature (JSRWT) holds significant scientific and societal importance. The present study unravels the counteracting impacts of El Niño–Southern Oscillation (ENSO) and the Aleutian low (AL) on JSRWT. Although ENSO and the AL have a significant positive correlation on interannual timescale, they exert totally opposite impacts on JSRWT. The positive Niño-3.4 sea surface temperature anomalies (SSTAs) usually lead to positive JSRWT anomalies, while an enhanced AL often results in negative JSRWT anomalies. The tropical convection anomalies associated with the positive Niño-3.4 SSTA induce two tropical to extratropical Rossby wave trains, leading to a barotropic anomalous anticyclone over northeast Asia, and thereby positive JSRWT anomalies. Conversely, the strengthened AL perturbs the westerly jet and induces an eastward-propagating Rossby wave train, leading to a barotropic anomalous cyclone over northeast Asia and negative JSRWT anomalies. The northeastward-propagating Rossby wave induced by the ENSO-related tropical convection anomalies over the Indian Ocean offsets the downstream Rossby wave induced by the strengthened AL, leading to counteracting impacts of ENSO and the AL on JSRWT. Finally, a novel index for monitoring JSRWT is proposed based on the indices of ENSO and AL.

Significance Statement
Despite the advantage of ENSO as a well-known predictability source, the seasonal predictability of Japan Sea Rim winter surface air temperature (JSRWT) is far from satisfactory. Here, we discovered that the Aleutian low (AL) has an independent influence on JSRWT contrasting with that of ENSO. When the AL and ENSO are in-phase, JSRWT shows no significant anomalies, but the JSRWT anomalies are largely amplified when AL and ENSO are out-of-phase. Therefore, a novel index for monitoring JSRWT is proposed based on the indices of ENSO and AL. These findings shed light on the low capacity of the seasonal prediction of JSRWT when only considering ENSO as the precursor.
Geostatistical Simulation of Daily Rainfall Fields—Performance Assessment for Extremes in West Africa
Authors: Rauch Manuel , Bliefernicht Jan , Maranan Marlon , Fink Andreas H. , Kunstmann Harald 
Published: August 2024

Abstract
The spatial description of high-resolution extreme daily rainfall fields is challenging because of the high spatial and temporal variability of rainfall, particularly in tropical regions due to the stochastic nature of convective rainfall. Geostatistical simulations offer a solution to this problem. In this study, a stochastic geostatistical simulation technique based on the spectral turning bands method is presented for modeling daily rainfall extremes in the data-scarce tropical Ouémé River basin (Benin). This technique uses meta-Gaussian frameworks built on Gaussian random fields, which are transformed into realistic rainfall fields using statistical transfer functions. The simulation framework can be conditioned on point observations and is computationally efficient in generating multiple ensembles of extreme rainfall fields. The results of tests and evaluations for multiple extremes demonstrate the effectiveness of the simulation framework in modeling more realistic rainfall fields and capturing their variability. It successfully reproduces the empirical cumulative distribution function of the observation samples and outperforms classical interpolation techniques like ordinary kriging in terms of spatial continuity and rainfall variability. The study also addresses the challenge of dealing with uncertainty in data-poor areas and proposes a novel approach for determining the spatial correlation structure even with low station density, resulting in a performance boost of 9.5% compared to traditional techniques. Additionally, we present a low-skill reference simulation method to facilitate a comprehensive comparison of the geostatistical simulation approaches. The simulations generated have the potential to provide valuable inputs for hydrological modeling.
Enhancing Surface Wind Speed and Temperature Prediction Using Surface-Layer Emulator and Transfer Learning
Authors: Feng Jin , Li Yanjie 
Published: August 2024

Abstract
Accurate prediction of surface wind speed and temperature is crucial for many sectors. Physical schemes in numerical weather prediction (NWP) and data-driven correction approaches have limitations due to uncertainties in parameterization and lack of robustness, respectively. This study introduces a physics-informed data model, PhyCorNet, which combines a deep learning–based physics emulator (PhyNet) and a subsequent correction network (CorNet). PhyNet imitates the revised surface-layer parameterization scheme [default option of the Weather Research and Forecasting (WRF) Model]. CorNet refines predictions by mitigating the difference between PhyNet and observations. PhyCorNet enables gridded forecasts despite the training data being point based. Therefore, PhyCorNet can be regarded as a rediagnostic scheme for surface wind speed at 10 m (WS10) and temperature at 2 m (T2). Compared to WRF, it reduced diagnostic root-mean-square errors in the 24-h forecasts for WS10 and T2 by 40% and 36%, respectively, across China, with unbiased forecasts at almost all sites. PhyCorNet addresses the oversmoothing prediction issue of other deep learning models by providing the ability to represent fine-scale features and perform well in statistically extreme samples. In grid cells without observations for training, PhyCorNet performed much better than WRF, demonstrating the zero-shot learning capability. This study implies that the emulator plus bias correction provided by PhyCorNet could be used as a simple but effective approach to improve the performance of other diagnostic quantities in NWP.

Significance Statement
We developed a new model called PhyCorNet to improve the surface wind speed and temperature forecasts. Existing weather forecast models have limitations in accurately predicting these variables. PhyCorNet first uses a neural network (PhyNet) to mimic an existing physics-based wind and temperature calculation method. Another neural network [correction network (CorNet)] improves the PhyNet forecasts by comparing them with observations. Across China, PhyCorNet reduced 24-h forecast errors for wind speed by 40% and temperature by 36% compared to a conventional model. It performed well under diverse conditions and overcame the oversmoothing issues faced by other machine learning models. Importantly, PhyCorNet outperformed traditional models in areas without historical observations. We suggest that this new framework can also be used to enhance the forecasts of other atmospheric variables.
Tranexamic Acid and Pulmonary Complications: A Secondary Analysis of an EAST Multicenter Trial
Authors: Raza Shariq S. , Tatum Danielle , Nordham Kristen D. , Broome Jacob M. , Keating Jane , Maher Zoe , Goldberg Amy J. , Chang Grace , Mendiola Pla Michelle , Haut Elliott R. , Tatebe Leah , Toraih Eman , Anderson Christofer , Ninokawa Scott , Maluso Patrick , Burruss Sigrid , Reeves Matthew , Coleman Lauren E. , Shatz David V. , Goldenberg-Sandau Anna , Bhupathi Apoorva , Spalding Chance , LaRiccia Aimee , Bird Emily , Noorbakhsh Matthew R. , Babowice James , Nelson Marsha C. , Jacobson Lewis E. , Williams Jamie , Vella Michael , Dellonte Kate , Hayward Thomas Z. , Holler Emma , Lieser Mark J. , Berne John D. , Mederos Dalier R. , Askari Reza , Okafor Barbara , Etchill Eric , Fang Raymond , Roche Samantha L. , Whittenburg Laura , Bernard Andrew C. , Haan James M. , Lightwine Kelly L. , Norwood Scott H. , Murry Jason , Gamber Mark A. , Carrick Matthew M. , Bugaev Nikolay , Tatar Antony , Duchesne Juan , Taghavi Sharven 
Published: August 2024

Background Anti-inflammatory effects of tranexamic acid (TXA) in reducing trauma endotheliopathy may protect from acute lung injury. Clinical data showing this benefit in trauma patients is lacking. We hypothesized that TXA administration mitigates pulmonary complications in penetrating trauma patients. Materials and Methods This is a post-hoc analysis of a multicenter, prospective, observational study of adults (18+ years) with penetrating torso and/or proximal extremity injury presenting at 25 urban trauma centers. Tranexamic acid administration in the prehospital setting or within three hours of admission was examined. Participants were propensity matched to compare similarly injured patients. The primary outcome was development of pulmonary complication (ARDS and/or pneumonia). Results A total of 2382 patients were included, and 206 (8.6%) received TXA. Of the 206, 93 (45%) received TXA prehospital and 113 (55%) received it within three hours of hospital admission. Age, sex, and incidence of massive transfusion did not differ. The TXA group was more severely injured, more frequently presented in shock (SBP < 90 mmHg), developed more pulmonary complications, and had lower survival ( P < 0.01 for all). After propensity matching, 410 patients remained (205 in each cohort) with no difference in age, sex, or rate of shock. On logistic regression, increased emergency department heart rate was associated with pulmonary complications. Tranexamic acid was not associated with different rate of pulmonary complications or survival on logistic regression. Survival was not different between the groups on logistic regression or propensity score–matched analysis. Conclusions Tranexamic acid administration is not protective against pulmonary complications in penetrating trauma patients.
Impact of Preoperative Osteosarcopenia and Postoperative Administration of Pancrelipase on the Prognosis of Borderline Resectable and Unresectable Locally Advanced Pancreatic Cancer
Authors: Matsumoto Michinori , Uwagawa Tadashi , Shirai Yoshihiro , Tsunematsu Masashi , Furukawa Kenei , Haruki Koichiro , Okui Norimitsu , Okazaki Kohei , Ishizaki Shunta , Ikegami Toru 
Published: August 2024

Background This study aimed to identify postoperative recurrence and prognostic factors, including osteosarcopenia for borderline resectable (BR) and unresectable locally advanced (UR-LA) pancreatic cancer and to examine the impact of postoperative pancreatic enzyme replacement therapy (PERT). Methods We retrospectively examined 32 resected patients with BR and UR-LA pancreatic cancer. We investigated independent factors in the disease-free survival and overall survival. The relation of osteosarcopenia with the clinicopathological factors was investigated. Additionally, the association of the administration of a standard dose of pancrelipase, the amount of lipase required for patients with pancreatic exocrine insufficiency, for ≥6 months postoperatively with improvement of sarcopenia, osteopenia, and osteosarcopenia and completion rate of adjuvant chemotherapy was investigated. Results Multivariate analyses identified osteosarcopenia ( P = 0.049) and lymph node metastasis ( P = 0.01) as independent recurrence predictors, and osteosarcopenia ( P = 0.002), maximum tumor diameter ≥40 mm ( P = 0.006), and no adjuvant therapy ( P = 0.01) as independent prognostic predictors. In the osteosarcopenia group, serum CA19-9 levels were higher ( P = 0.03). The administration of a standard dose of pancrelipase for ≥6 months postoperatively was none in the osteosarcopenia group (0% vs 42.9%, P = 0.01), while significantly improved postoperative sarcopenia (33% vs 0%, P = 0.004), increased number of cycles of adjuvant chemotherapy (n = 6 vs n = 3, P = 0.03), and the completion rate of adjuvant chemotherapy in excluding cases interrupted because of recurrence (86% vs 25%, P = 0.007). Conclusions Osteosarcopenia was an independent recurrent and prognostic factor in patients after pancreatectomy for locally advanced pancreatic cancer. Appropriate postoperative PERT may contribute to a better prognosis by improving sarcopenia and increasing the completion rate of adjuvant chemotherapy.
Evaluation of drilling by induced delamination of hybrid biocomposites reinforced with natural fibers: A statistical analysis by RSM
Authors: Elhadi Abdelmalek , Amroune Salah , Slamani Mohamed , Jawaid Mohammad , Koklu Ugur , Bidi Tarek 
Published: August 2024

Studying the drilling of a hybrid jute/palm composite material offers significant contributions to sustainable material development. Incorporating renewable jute and palm fibers represents an innovative, eco-friendly approach compared to synthetic composites. This research aims to optimize drilling parameters to reduce defects and evaluate the performance of different drilling tools, crucial for industrial applications. Drilling is performed via three different types of drills bit: High-Speed Steel, HSS-Co5 coated high-speed steel with 5% cobalt, and carbide. The drilling process involves adjusting the feed and rotational speed. Response Surface Methodology (RSM) was used to select drilling settings by validating experimentally obtained data and predicting the behavior of the structure based on cutting circumstances. The findings indicated that the most effective cutting parameters for minimizing delamination are achieved using the HSS drill bit, namely at lower feed and rotational speeds. Delamination remains below the threshold of 1.106 when the feed is 0.04 mm/rev and the rotational speed is 1592 rpm. The analysis of the results obtained using the response surface methodology indicates that the R2 coefficient for cylindricity is 0.96%. In contrast, the rate of delamination is 0.79% and the rate of circularity is 0.89%.
Effect of Diurnal Light Conditions on Electroretinogram Responses to Red and Blue Flickering Light
Authors: Kozaki Tomoaki , Takao Motoharu 
Published: August 2024

Bright light impacts the human circadian system such that exposure to bright light at night can suppress melatonin secretion, and exposure to bright light in the morning prevents light-induced melatonin suppression at night. The preventive effect of morning light may attenuate the prior history of light sensitivity of intrinsically photosensitive retinal ganglion cells (ipRGCs) that regulate the circadian system. In this study, we evaluated electroretinogram (ERG) responses to red and blue flickering lights following dim and bright daylight conditions. Eleven healthy females underwent ERG measurements during exposure to 33 Hz flickering red or blue light under dim and bright daytime conditions. We averaged ERG waves for 50 flickering light pulses of the trigger signal data. We obtained the amplitude of the signal-averaged ERG by calculating the difference between the waves’ peaks and bottoms. Although there was no significant dim and bright light difference in the amplitude of ERG waves, the ERG amplitude to flickering blue light under the bright light condition was significantly lower than to flickering blue light under the dim light condition. In this study, blue light stimulated mainly ipRGCs and S-cones. Since S-cones may contribute minimally to the light-adapted 33 Hz flicker ERG results, our findings suggest that bright light during the daytime attenuates the sensitivity of human ipRGCs.
ChatGPT Goes to College: Exploring Student Perspectives on Artificial Intelligence in the Classroom
Authors: Cavazos Jenel T. , Hauck Keane A. , Baskin Hannah M. , Bain Catherine M. 
Published: August 2024

Background The emergence of artificial intelligence (AI) in higher education has sparked numerous discussions about its implications. ChatGPT, a prominent AI conversational model, has attracted significant attention for its ability to generate essays and formulate responses. Objective The current study sought to explore how and why students are using ChatGPT, and to examine their perceptions about ChatGPT and academic integrity. Method Students were surveyed about the frequency and motivation for ChatGPT use and their views on ChatGPT and academic misconduct. Exploratory factor analyses were conducted to examine patterns of correlations between each of the measures. Results Students primarily use ChatGPT for gathering information, motivated by its value and convenience rather than hedonic reasons, and can correctly identify academically unethical uses of the tool as cheating. Conclusion The current study presents comprehensive data on college students’ ChatGPT usage patterns, attitudes, and perceptions of cheating behavior. The outcomes of this research provide insight into how college students are currently interacting with AI tools. Teaching Implications Our findings offer practical insights for universities developing AI policies in the classroom, contributing to the ongoing discourse on AI’s role in higher education by providing accurate information about ChatGPT’s pervasiveness in academia.