bluuebunny/crossref_metadata_2025_split huggingface dataset:
The recognition of typical and variant histological categories of Nodular lymphocyte predominant Hodgkin lymphoma/B-cell lymphoma have high reproducibility, but challenges in classifying each variant remain
Authors: de Castro João Víctor Alves , Crespigio Jefferson , Olivera Cristiano Claudino , Costa Felipe D’Almeida , Ferreira Cristiane Rúbia 
Published: September 2023

Abstract
Background: Nodular lymphocyte predominant Hodgkin Lymphoma/B-cell lymphoma (NLPHL/NLPBL) comprises around 5% of Hodgkin Lymphomas. It is characterized by the presence of lymphocyte predominant cells scattered throughout nodular areas of neoplastic follicles. Six morphological growth patterns with prognostic impact are recognized and grouped as “typical” (“A” and “B”) and “variant” (“C”, “D”, “E”, and ”F”) patterns. These patterns also aid in distinct differential diagnosis considerations. Due to its rarity, morphological and immunohistochemical studies are essential to make progress in the classification of such patterns. The study aims to describe the growth patterns of NLPHL/NLPBL diagnosed in a Brazilian Cancer Center, including immunoarchitectural characteristics of both the tumor cells and the microenvironment, and evaluate reproducibility of typical versus variant pattern diagnosis by general pathologists.
Methods: Retrospective histopathological study with cases diagnosed as NLPHL/NLPBL between 2014 and February 2022. Histopathological review for diagnostic confirmation and evaluation of growth patterns was performed by two general pathologists, and a Cohen’s kappa concordance level was evaluated. Cases with major diagnostic discordance were reviewed during a consensus meeting by one or two hematopathologists.
Results: Fifty cases of 45 patients were retrieved, including excisional biopsies (36/50, 72,0%) and core biopsies (14/50, 28,0%). Typical growth patterns were the most frequently encountered primary pattern (27/47, 57,4%); among the variant patterns, pattern “E” was the most frequent (9/20, 45,0%). Pattern “F” was not identified, and 3 core biopsies could not be evaluated. Cohen’s kappa was 0.894. There were 3 discordant cases, where challenges were related to small sampling in incisional biopsies and difficulties in differentiating pattern “C” from pattern “E”. T-cell PD1+ rosettes were seen in 92,6% of cases (25/27), being positive for CD4 (16/19, 84,2%) and BCL6 (24/31, 77,4%).
Conclusion: The identification of typical and variant growth patterns of NLPHL/NLPBL is highly reproducible by general pathologists. These patterns characterize distinct prognostic subgroups and aid in differential diagnostic considerations for specific immunoarchitectural scenarios. Further studies are needed to deepen the understanding of the different microenvironment of each pattern at the molecular level, aiming to uncover novel diagnostic and prognostic markers.
Optimization of a recombinant BlaR-CTD protein formulation using the Response Surface Methodology
Authors: Abdolvahab Mohadeseh Haji , Safari Mojdeh , Hasannejad Farkhonde , Asefi Nika , Salimi Alireza , Nazari Mahboobeh 
Published: September 2023

Abstract
A penicillin-binding protein (PBP) is a group of proteins that have an affinity for and bind to penicillin. They are a normal component of many bacteria and play a crucial role in bacterial cell wall synthesis. PBPs are the targets of β-lactam antibiotics, such as penicillin. The sequence of a carboxy-terminal of the β-lactam sensor-transducer protein (BlaR-CTD) from Bacillus licheniformis ATCC14580 was extracted from US7745193B2 patent and expressed in E. coli using pColdI vector as a soluble His-tag recombinant protein. In this study, several excipients were used to improve the stability of recombinant BlaR-CTD and obtain the optimal formulation for this protein using response surface methodology (RSM)/ Central Composite Design (CCD). Total protein concentration was measured by UV spectroscopy and Bradford test. A total of 7 various formulations were designed using four different excipients including Glycerol, Sucrose, Triton x-100 and Tween-20, and three different buffers like Tris, Borate and PBS. By obtaining suitable excipients and buffer i.e. glycerol and sucrose, several concentrations of pH 7 to 9 were evaluated. The pH 7.62, glycerol 15.35% and sucrose 152.52 mM were determined as the most suitable for improve thermal stability of recombinant BlaR-CTD.
The role of tax regulation on private consumption: An analysis based on China's Tax System Structure
Authors: Sun Shiqiang , Lv Pingzhang 
Published: September 2023

Abstract
How does tax regulation affect private consumption? We establish an individual consumption model and use provincial-level panel data in China to empirically test the relationship between China's tax system structure and private consumption. The results indicate that China's turnover tax has a inhibitory effect on private onsumption level and consumption structure upgrading, but personal income tax has a promoting effect on private consumption level and consumption structure upgrading, while property tax has the most significant promoting effect on private consumption level and onsumption structure upgrading. Further research suggests that turnover tax and property tax have a significant spatial spillover effect on private consumption structure, and the indirect effect is more obvious than the direct effect. Moreover, the impact of these three types of taxes on China's rural consumption structure is greater than that of urban areas. The research conclusions can provide reference basis for public policy formulation in China and some developing countries.
ODRL: Application of Reinforcement Learning in Priority Scheduling for Running Cost Optimization
Authors: Kuang Cheng , Duan Meng , Lv Tao , Wu Yingjun , Ren Xiangyu , Wang Luping 
Published: September 2023

Abstract
Due to the heterogeneity of workloads and the randomness and complexity of hybrid scheduling environment, How to address the challenge of minimizing data center running costs while ensuring workloads SLA has emerged as a significant research problem. To address this, we propose an Optimal Deep Reinforcement Learning Model for Running Cost Optimization in Hybrid Environments (ODRL). Firstly, we propose Running Cost Model (RCM) that analyzes data center operating costs from two perspectives based on different running patterns of the workload and node affinity constraints: minimizing computing node utilization and resource operating costs. Subsequently, we propose a Priority-Aware Scheduling Algorithm based on Deep Reinforcement Learning(PASD) that use AHP-TOPSIS to quantify workload characterization, get real-time feedback for environment and update historical experience through prioritized experience replay. Finally, extensive experimental results validate the effectiveness of the proposed model. In comparison to Kube-Scheduler, ODRL achieves a significant 15% improvement in reducing data center running cost. Additionally, there is a 7.8% increase in CPU utilization and a 16.7% increase in memory utilization.
Extending Convolution to Semantic Segmentation with Graph Neural Networks
Authors: Armstrong Sholto John Nicky , Grobler Hans 
Published: September 2023

Abstract

Scene understanding enables multiple applications such as robotic automation. To enable scene understanding, semantic segmentation is an essential component. Highly accurate per-voxel semantic labels can efficiently be obtained through the use of encoder-decoder Convolutional Neural Networks (CNNs). However, scene understanding requires instances of objects to be discovered in a scene. Per-voxel labelling is unable to distinguish between separate instances of a given object. A novel method is proposed that enables segment-level predictions to be formed from the voxel-level predictions provided by the CNN architecture. This method uses an existing 3D CNN architecture to provide rich and computationally inexpensive features. The scene is then segmented with a graph-based segmentation technique to identify objects in the scene. Finally, a graph-based neural network is used to capture hierarchical information improving overall accuracy. The approach is tested on the S3DIS and ScanNet datasets to provide a comparable baseline to more modern architectures.
Landau damping and the survival threshold
Authors: Nguyen Toan 
Published: September 2023

Abstract
In this paper, we establish the large time asymptotic behavior of solutions to the linearized Vlasov-Poisson system near general spatially homogenous equilibria $\mu(\frac12|v|^2)$ with connected support on the torus $\mathbb{T}^3_x \times \RR^3_v$ or on the whole space $\RR^3_x \times \RR^3_v$, including those that are non-monotone. The problem can be solved completely mode by mode for each spatial wave number, and their longtime dynamics is intimately tied to the ''survival threshold'' of wave numbers computed by $$\kappa_0^2 = 4\pi \int_0^\Upsilon \frac{u^2\mu(\frac12 u^2)}{\Upsilon^2-u^2} \;du$$ where $\Upsilon$ is the maximal speed of particle velocities. It is shown that purely oscillatory electric fields exist and obey a Klein-Gordon's type dispersion relation for wave numbers below the threshold, thus confirming the existence of Langmuir's oscillatory waves known in the physical literature. At the threshold, the phase velocity of these oscillatory waves enters the range of admissible particle velocities, namely there are particles that move at the same propagation speed of the waves. It is this exact resonant interaction between particles and the oscillatory fields that causes the waves to be damped, classically known as Landau damping. Landau's law of decay is explicitly computed and is sensitive to the decaying rate of the background equilibria. The faster it decays at the maximal velocity, the weaker Landau damping is. Beyond the threshold, the electric fields are a perturbation of those generated by the free transport dynamics and thus decay rapidly fast due to the phase mixing mechanism.
Urban Heat Variation and Temperature Lapse Rate in the Kathmandu Valley
Authors: Thapa Nabin , Baniya Binod , Bhusal Bhawana , Sigdel Madan , Khanal Kripa , Acharya Ram Hari 
Published: September 2023

Abstract
The rate of urbanization growth has accelerated and made urban areas comparatively warmer than surroundings which are the main issues of urban heat worldwide. The Kathmandu Valley is one of the million plus cities with the fastest rate of urbanization and consequent extreme heat. In this study, urban heat was analyzed using both in-situ and satellite-based observation and estimated temperature lapse rate. The Mann Kendell test, Sen’s slope, raster image analysis and lapse rate estimation methods were used. The results showed that average temperature difference in between urban core and surrounding was 4.07oC from 1990 to 2020. Likewise, the summer day temperature in Putalisadak was 8.8oC higher than the Nagarkot. The maximum temperature has increased in all stations where Godavari station has increased significantly (0.073oC yr− 1, p < 0.0001). During all seasons, the daytime temperature is higher than the nighttime temperature which is more influenced by the humidity. The maximum 32.86oC daytime temperature was recorded on August 4, 1pm and the minimum temperature was 3.67oC on Jan 20, 6am, 2020 at the city core. Similarly, the highest temperature was recorded at 31oC in Bagbazar and 33oC in Patan on July 10 and July 11, 2022 respectively when the humidity was lower. Satellite-based observation also shows that the urban heat scenario of the Kathmandu Valley was higher in the urban core which was ranges from 21.06 to 26.09 during 2000–2020. The temperature of the city has increased. However, temperature lapse rate in response to Nagarkot (reference station) is normal i.e decreased temperature in response to increased height. The higher lapse rate is generally found in the Godavari and lower was observed in the Machhegaoun. Overall, the Kathmandu Valley is getting more warmer compared to the surroundings. This comprehensive study is useful to explore the understanding of urban heat islands and temperature lapse rate in the major cities in compared to the surroundings in Nepal.
Impact assessment of onchocerciasis through lymphatic filariasis transmission assessment surveys using Ov-16 rapid diagnostic tests in Sierra Leone
Authors: Kargbo-Labour Ibrahim , Bah Mohamed S. , Conteh Abdulai , Melchers Natalie V.S. Vinkeles , Redwood-Sawyerr Victoria , Stolk Wilma A. , Paye Jusufu , Sonnie Mustapha , Veinoglou Amy , Koroma Joseph B. , Hodges Mary H. , Weaver Angela M. , Zhang Yaobi 
Published: September 2023

Abstract
Background
Sierra Leone is endemic with onchocerciasis in 14 of its 16 districts with high prevalence (47–88.5%) by skin snips at baseline. After 11 rounds of mass treatment with ivermectin with good coverage, an impact assessment was conducted in 2017 to assess the progress towards onchocerciasis elimination in the country.
Methods
A cluster survey was conducted, either integrated with lymphatic filariasis (LF) transmission assessment survey (TAS) or standalone with the LF TAS sampling strategy, in 12 (now 14) endemic districts. Finger prick blood samples of randomly selected children in Grades 1–4 were tested in the field using the SD Bioline Onchocerciasis IgG4 rapid tests.
Results
In total, 17,402 children aged 4–19 years in 177 schools were tested and data from 17,364 children aged 4–14 years (14,230 children aged 5–9 years) were analyzed. There were 346 children confirmed positive for Ov-16 IgG4 antibodies, a prevalence of 2.0% (95% CI: 1.8–2.2%) in children aged 4–14 years with prevalence increasing with age. Prevalence in boys 2.4% (95% CI: 2.1–2.7%) was higher than in girls 1.6% (95% CI: 1.4–1.9%). There was a trend of continued reduction from baseline and 2010. Using data from children aged 5–9 years, overall prevalence was 1.7% (95% CI: 1.5–1.9%). The site prevalence ranged from 0–33.3% (median prevalence = 0.0%): <2% in 127 schools, 2% – <5% in 34 schools and ≥ 5% in 16 schools. There was a significant difference in average prevalence between districts. Using spatial analysis, the Ov-16 IgG4 antibody prevalence was predicted below 2% in coastal areas and in the large parts of Koinadugu, Bombali and Tonkolili districts while high prevalence (> 5%) was predicted in some focal areas, centered in Karene, Kailahun, and Moyamba/Tonkolili.
Conclusions
Low Ov-16 IgG4 antibody prevalence was shown in most areas across Sierra Leone. In particular, low seroprevalence in 5–9 years old suggests that the infection was reduced to a low level after 11 rounds of treatment intervention. Sierra Leone has made major progress towards elimination of onchocerciasis. However, attention must be paid to those high prevalence focal areas.
Birth Outcomes among People with Hepatitis C in Pregnancy — Three U.S. States, 2018-2020
Authors: Woodworth Kate R. , Newton Suzanne M. , Tannis Ayzsa , Reynolds Megan R. , Olsen Emily O. , Sizemore Lindsey , Wingate Heather , Orkis Lauren , Reynolds Bethany , Longcore Nicole , Thomas Nadia , Kim Shin Y. , Panagiotakopoulos Lakshmi , Wester Carolyn , Delman Dana Meaney , Gilboa Suzanne M. , Tong Van T. 
Published: September 2023

Abstract

There are limited and conflicting data regarding the impact of hepatitis C in pregnancy on adverse birth outcomes. Using a large surveillance cohort, we describe birth outcomes among a cohort of people with HCV in pregnancy. Among 1171 infants, the proportion born preterm was 19%, 13% were small-for-gestational age and 26% of term infants required intensive care. Assessments of recent changes to recommendations for HCV screening in pregnancy should evaluate the impact on maternal access to care for both HCV treatment as well as comorbidities such as substance use disorder which may contribute to adverse birth outcomes.
Magnitude of caesarean section delivery and its associated factor among immediate postnatal women in public hospitals of Addis Ababa in 2022
Authors: lambebo Abera , Getaneh Chala , Mezemir Yordanos , G/mariam Muluken 
Published: September 2023

Abstract

Background Caesarean section is the commonest obstetric operative procedure worldwide. Including Ethiopia, that can improve infant and maternal outcomes.
Objective The objective of this study is to compute the magnitude of cesarean section delivery rate and its associated factors among immediate postnatal women in public hospitals of Addis Ababa, Ethiopia 2022.
Methods An institution-based cross-sectional study design was conducted. A total of 550 study participants were chosen using multi-stage sampling. A self-administered structured questionnaire was used for data collection; the collected data was cleared and entered into Epi Data version 3.1. Then it was exported to SPSS version 20 for analysis. Then, the result will be presented by table frequency, percentage, and charts. By using binary logistic regression, bivariate analysis and multivariate analysis were computed to see the association between each independent variable and the outcome variable. Adjusted odds ratios with their 95% confidence intervals and a p-value of less than 0.05 will be used to declare a result as statistically significant.
Results According to these results (n=550), the prevalence of cesarean sections was 45.8%, with a 95%CI of 42%–50.2%). Previous caesarean section (AOR = 15.32, 95% CI: (7.07-33.17)), eclampsia/pre eclampsia (AOR 10.69, 95% CI: (4.99-22.87)Fetal distress CS (AOR = 6.28, 95% CI: (2.98-13.24), APH (AOR = 3.13, 95% CI: (1.33-9.65), and mal presentation (AOR = 2.96, 95% CI: 14.2-6.18) were all significantly associated with caesarean section birth.
Conclusion In this study the rate of Caesarean delivery is unacceptably high Previous Cesarean section deliveries and Pre-eclampsia /eclampsia are the most significant factors for cesarean delivery. CS utilizations higher than WHO recommendation was not associated with a reduction in maternal and newborn mortality rates, Empowering and educating women, increasing co-services targeting mothers’ awareness might be very vital to deal with current problem.
Building footprint data for countries in Africa: to what extent are existing data products comparable?
Authors: Chamberlain Heather R , Darin Edith , Adewole Ademola , Jochem Warren Christopher , Lazar Attila N , Tatem Andrew J 
Published: September 2023

Abstract

Growth and developments in computing power, machine-learning algorithms and satellite imagery spatiotemporal resolution have led to rapid developments in automated feature-extraction. These methods have been applied to create geospatial datasets of features such as roads, trees and building footprints, at a range of spatial scales, with national and multi-country datasets now available as open data from multiple sources. Building footprint data is particularly useful in a range of applications including mapping population distributions, planning resource distribution campaigns and in humanitarian response. In settings with well-developed geospatial data systems, such datasets may complement existing authoritative sources, but in data-scarce settings, they may be the only source of data. However, knowledge on the degree to which building footprint data products are comparable and can be used interchangeably, and the impact of selecting a particular dataset on subsequent analyses remains limited. For all countries in Africa, we review the available multi-country building footprint data products and analyse their similarities and differences in terms of building area and count metrics. We explore the variation between building footprint data products across a range of spatial scales, including sub-national administrative units and different settlement types. Our results show that the available building footprint data products are not interchangeable. There are clear differences in counts and total area of building footprints between the assessed data products, as well as considerable spatial heterogeneity in building footprint coverage and completeness.
Empirical Relationship between Use, Area, and Ambient Air Concentration of Methyl Bromide
Authors: Li LinYing , Johnson Bruce , Segawa Randy 
Published: September 2023

ABSTRACTMethyl bromide (MeBr) is one of the most widely used soil fumigants. Human exposure to MeBr above threshold values can cause serious health problems. The exposure assessment of MeBr depends on estimation or measurement of its air concentrations. This study proposed a methodology for systematically exploring the empirical relationship between MeBr use intensity and ambient air concentrations. Monitored air concentrations were regressed to MeBr use over various spatiotemporal scales that step‐wise increased around the monitoring site and monitoring period. The results showed that the goodness‐of‐fit varied with the spatiotemporal scale of MeBr use. The best fit was Y = 0.46 + 0.00120X (R2 = 0.95, n = 11), where Y was the 8‐wk average ambient air concentration (μg/m3), and X was the weekly average use (kg/wk) over an area of 11.3 × 11.3 km (7 × 7 mi). The model was calibrated with air‐monitoring data and use data of 2000, and verified with the same type data of 2001. The model estimated subchronic air concentration with reasonable accuracy.
Machine-learning oxybarometer developed using zircon trace-element chemistry and its applications
Authors: Zou Shaohao , Brzozowski Matthew J. , Chen Xilian , Xu Deru 
Published: September 2023

Abstract
Magmatic oxygen fugacity (fO2) is a fundamental property to understanding the long-term evolution of the Earth’s atmosphere and the formation of magmatic-hydrothermal mineral deposits. Classically, the magmatic fO2 is estimated using mineral chemistry, such as Fe-Ti oxides, zircon, and hornblende. These methods, however, are only valid within certain limits and/or require a significant amount of a priori knowledge. In this contribution, a new oxybarometer, constructed by data-driven machine learning algorithms using trace elements in zircon and their corresponding independent fO2 constraints, is provided. Seven different algorithms are initially trained and then validated on a data set that was never utilized in the training processes. Results suggest that the oxybarometer constructed by the extremely randomized trees model has the best performance, with the largest R2 value (0.91 ± 0.01), smallest RMSE (0.45 ± 0.03), and low propagated analytical error (~0.10 log units). Feature importance analysis demonstrates that U, Ti, Th, Ce, and Eu in zircon are the key trace elements that preserve fO2 information. This newly developed oxybarometer has been applied in diverse systems, including arc magmas and mid-ocean ridge basalts, fertile and barren porphyry systems, and global S-type detrital zircon, which provide fO2 constraints that are consistent with other independent methods, suggesting that it has wide applicability. To improve accessibility, the oxybarometer was developed into a software application aimed at enabling more consistent and reliable fO2 determinations in magmatic systems, promoting further research.