bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of Intergrowth-21 and Fenton Charts for Extrauterine Growth in Very Low Birth Weigth Infants
Authors: Turktan Ilkyaz , Erdeve Omer , Kostekci Ezgi , Okulu Emel , Atasay Begum , Arsan Saadet 
Published: January 2024

Abstract
Background: The growth of premature babies is expected to be equivalent to healthy fetal growth, but this is rarely achieved in practice. It is predicted that many premature babies, especially severe premature babies, will be discharged with growth restriction. Extrauterine growth retardation (EUGR), which was developed as a definition for this purpose, is defined as being below the 10th percentile according to the growth curve at discharge at the corrected 36th/40th gestational week or the difference between birth and discharge z-score being >1 SD. The aim of our study is to reveal the differences between Intergrowth-21 lie Fenton curve in the evaluation of extrauterine growth.
Methods: Infants under 1500 g who were born in Ankara University Neonatal Intensive Care Unit between January 1, 2015 and December 31, 2019 or transferred in the first 24 hours were included. Infants with major congenital anomalies, unknown gestational age, chromosomal anomalies, hydrops fetalis, TORCH infection, infants of substance-abusing mothers and infants who died during hospitalization were excluded.
Results: According to the Fenton chart, the rate of EUBG at discharge was 66.3%. There was no significant difference between the groups with and without EUGR in gender, gestational diabetes, maternal smoking during pregnancy, placental abruption, magnesium prophylaxis, development of respiratory distress and the need for intubation in the first 3 postnatal days.
When the patients were grouped according to birth weight, the highest rate of EUGR according to the Fenton chart was found in the group with a birth weight ≤1000 g (78.8%) (p=0.036). The proportion of patients defined as SGA by the Intergrowth-21 was significantly higher than the Fenton chart (p<0.001). When EUGR rates according to body weight were evaluated in Fenton and Intergrowth-21 charts; EUGR rate was found to be higher than Fenton (p<0.001). When the mean z-scores of body weight, height and head circumference calculated according to Fenton and Intergrowth-21 charts at birth and discharge were compared, it was observed that body weight and height z-scores at birth and discharge were significantly lower in the negative direction in the Intergrowth-21 (p<0.001). Head circumference z-score was found to have higher values in the Fenton chart than in the Intergrowth-21 at birth and discharge (p<0.001).
Conclusions: The results show that when Intergrowth-21 and Fenton charts are compared, the Intergrowth-21 is more sensitive in defining the SGA rate. The Fenton chart is more sensitive in defining EUBG at discharge. These differences observed between the charts make growth monitoring of premature infants and follow-up of comorbidities difficult. Therefore, establishing ideal growth curves is of great importance both during hospitalization and post-discharge follow-up of premature infants.
Cover-Source Mismatch in Steganalysis: Systematic Review
Authors: Mallet Antoine , Benes Martin , Cogranne Rémi 
Published: January 2024

Abstract

Operational steganalysis contends with a major problem referred to as the cover-source mismatch (CSM),
which is essentially a change of distribution caused by different parameters and settings over training and test data.
Despite it being of fundamental importance in operational context, the CSM problem is often overlooked in the literature.
With the goal to increase the visibility of this problem and attract the interest of the community,
the present paper proposes a systematic review of the literature.
It summarizes gathered knowledge and major open questions over the last 20 years of active research on CSM:
terminology, methods of measurement, known causes, and mitigation strategies.
Over 100 papers exploring, mitigating, assessing or discussing steganalysis
under train-test mismatch were collected by sampling scholar databases, and tracing references, cited and generated.
For image steganalysis, the literature provided enough evidence to quantify the impact of causes,
and the effectiveness of mitigation strategies.
WITHDRAWN: Influence of carbonization process parameters on copper (II) ion adsorption performance of biochar from exhausted coffee husk (ECH)
Authors: Das S. K. 
Published: January 2024

Abstract

Biochar derived from agro industrial waste has been considered as promising green adsorbent due to its significant availability and affordable production This study investigated and evaluated the adsorption performance of biochar from exhausted coffee husk (ECH). The influence of carbonization process parameter, namely temperature (300, 400, 500, 600°C), residence time (30, 60 and 120 minutes), and rate (5, 10, 15°C/min) on the removal of copper (II) ion (Cu2+) at different biochar dosages (0.2, 4, 0.6, 0.8, 1 g) were investigated. The increasing of carbonization temperature, residence time, rate and biochar dosage showed different adsorption characterization on Cu2+ The carbonization temperature of 600°C resulted in highest removal efficiency of 92%. Furthermore, surface analyzer Brunauer-Emmett-Teller (BET) was used to characterize the adsorbent while and Scanning Electron Microscope (SEM) was used to observe the surface morphology of biochar at the different carbonization The results showed that the carbonization temperature affected the surface area of the ECH
Occurrence and Ecological Risk of Pharmaceutical Compounds in Water Samples From Obuasi Metropolis of Ghana
Authors: Azanu David , Arthur Charles Ato , Adu-Poku David , Adu Abenaa Owusuwaa , Oppong Agnes , Alemya Timothy Abane 
Published: January 2024

Abstract

The occurrence of pharmaceutical compounds in surface water is of global concern. Therefore, this study was conducted to assess the occurrence of acetaminophen, caffeine, ibuprofen, diclofenac, aspirin, diazepam, and tramadol in water samples from hospitals, waste stabilisation ponds, and river in the Obuasi metropolis, Ghana. Solid phase extraction (SPE) sample preparation followed by analysis using high-performance liquid chromatography (HPLC) method was performed on the water samples. The removal efficiency of these pharmaceuticals by waste stabilisation ponds in the study area was also determined. Finally, the ecological risk posed by pharmaceuticals analysed was estimated as risk quotient (RQ). All seven pharmaceuticals analysed were found in all hospital effluent, waste stabilisation ponds, and surface water, indicating their occurrence in the aquatic systems in Obuasi municipality. Acetaminophen was the most prevalent compound found in this study, with a maximum concentration of 23.0 µg/L, while diazepam was the least pervasive compound, with a maximum concentration of 2.0 µg/L. The percentage removal efficiency of the waste stabilisation pond ranged from 61.5 to 82.2%. The RQs ranged from 0.0 to 0.191 for surface water, 0.0002 to 0.209 for waste stabilization pond water, and 0.0–0.295 for hospital wastewater. This indicates that the RQ for all pharmaceuticals analysed could pose low to medium risk. This study has revealed the occurrence and estimated the possible threat posed by these pharmaceuticals; thereby staking a justifiable claim for an urgent action against the removal of pharmaceuticals in water. ,
A Novel 3D Distributed Energy Efficient Clustering Algorithm for Underwater Acoustic Wireless Sensor Network
Authors: Lakshmi Kadali , Hossain Ashraf , Mummaneni Kavicharan 
Published: January 2024

Abstract

Underwater acoustic communication is a unique and challenging area, particularly in terms of designing a network topology with low energy consumption, minimal delay, and an extended network lifetime. Energy efficiency is a challenging problem in the design of underwater acoustic wireless sensor networks (UAWSN) because of the limited energy availability from batteries and the difficulty of replacing these batteries. However, it is necessary to design network placement, cluster selection, and routing to extend the network lifetime by reducing energy consumption. In this study, the Three-Dimensional Distributed Energy Efficient Clustering (3D-DEEC) algorithm is proposed for optimizing energy efficiency and prolonging network life through the utilization of clustering techniques. The proposed algorithm considers multiple factors, such as cluster head (CH) selection, distance between the base station and each sensor node, total transmitting energy, residual energy of each node, and time delay. Compared with existing clustering schemes, 3D-DEEC not only increases the efficiency of the network, but also prolongs the network lifetime and improves network integrity with optimum packet delivery ratio, minimizing energy consumption and improving network coverage area. The proposed algorithm is designed to achieve optimum three-dimensional clustering scheme for the UAWSN in terms of energy efficiency in hostile underwater acoustic environments.
Preoperative clinical radiomics model based on deep learning in prognostic assessment of patients with gallbladder carcinoma
Authors: Jin Zhechuan , Li Qi , Zhang Jingwei , Chen Chen , Zhang Dong , Yang Min , Wang Qiuping , Cai Zhiqiang , Si Shubin , Geng Zhimin 
Published: January 2024

Abstract
Objective
We aimed to develop a preoperative clinical radiomics survival prediction model based on the radiomics features via deep learning to provide a reference basis for preoperative assessment and treatment decisions for patients with gallbladder carcinoma (GBC).
Methods
A total of 168 GBC patients who underwent preoperative upper abdominal enhanced CT from one high-volume medical center between January 2011 to December 2020 were retrospectively analyzed. The region of interest (ROI) was manually outlined by two physicians using 3D Slicer software to establish a nnU-Net model. The DeepSurv survival prediction model was developed by combining radiomics features and preoperative clinical variables.
Results
A total of 1502 radiomics features were extracted from the ROI results based on the nnU-Net model and manual segmentation, and 13 radiomics features were obtained through the 4-step dimensionality reduction methods, respectively. The C-index and AUC of 1-, 2-, and 3-year survival prediction for the nnU-Net based clinical radiomics DeepSurv model was higher than clinical and nnU-Net based radiomics DeepSurv models in the training and testing sets, and close to manual based clinical radiomics DeepSurv model. Delong-test was performed on the AUC of 1-, 2-, and 3-year survival prediction for the two preoperative clinical radiomics DeepSurv prediction models in the testing set, and the results showed that the two models had the same prediction efficiency (all P > 0.05).
Conclusions
By using the DeepSurv model via nnU-Net segmentation, postoperative survival outcomes for individual gallbladder carcinoma patients could be assessed and stratified, which can provide references for preoperative diagnosis and treatment decisions.
Bayesian Change Point Detection via a General Sparse Recursive Filter
Authors: Lu Shaochuan 
Published: January 2024

Abstract
We propose a sparse recursive filtering method for Bayesian multiple change point detection. The sparse recursive filtering is generally applicable when either conjugate priors or nonconjugate priors are elicited. This approach is also applicable when either cross-segment dependence or cross-segment independence occurs. The computational and storage costs of the forward-filtering backward-sampling (FFBS) algorithm are quadratic to the number of uniformisation times generated by the uniformisation scheme. We demonstrate the methods through simulation studies and real data analysis in these scenarios.
Impact of Spatial Functional Division in Urban Agglomeration on Urban Carbon Emissions: An Empirical Study of 19 Urban Agglomerations in China
Authors: Chen Haijiang , Wang Yunsong , Zhang Songlin 
Published: January 2024

Abstract
This paper empirically examines the impact of spatial functional division in urban agglomeration on carbon emissions in Central and Peripheral City using data from 19 urban agglomerations in China spanning from 2010 to 2019. The findings indicate that: (1) The spatial functional division in urban agglomeration contributes to a reduction in carbon emissions in Central City but exacerbates them in Peripheral City. (2) Technological progress partially mediates the effect of spatial functional division in urban agglomeration on carbon emission reduction in Central City, while both technological progress and manufacturing agglomeration have partial mediating effects on the increase of carbon emissions due to spatial functional division in urban agglomeration in Peripheral City. (3) Industrial collaborative agglomeration and digital economy enhance the carbon emission reduction effect of spatial functional division in urban agglomerations for Central City; however, industrial collaborative agglomeration mitigates the exacerbating role of spatial functional division in urban agglomeration on carbon emissions for Peripheral City. (4) The impact of spatial function division in urban agglomeration on carbon emissions exhibits regional heterogeneity within urban agglomerations. The findings hold certain reference significance for relevant countries when formulating public policies that strike a balance between economic development and carbon emissions amidst deepening of spatial functional division in urban agglomeration.
Mobile-Aware Task Offloading Strategy in Large-Scale Asynchronous Mobile Edge Computing based on a Hybrid Deep Q-learning and an Index Policy Scheme
Authors: Wang Jinpeng , Meng Qingyong , Kang Yufang , Gillbanks Jeremy , Zhao Xin 
Published: January 2024

Abstract
Mobile-edge computing (MEC) offloads computational tasks from wireless devices to network edge, and enables realtime information transmission and computing. Most existing work concerns a small-scale synchronous MEC system. In this paper, we focus on a large-scale asynchronous MEC system with random task arrivals, distinct workloads, and diverse deadlines. We formulate the offloading policy design as a restless multi-armed bandit (RMAB) to maximize the total discounted reward over the time horizon. However, the formulated RMAB is related to a PSPACE hard sequential decision-making problem, which is intractable. To address this issue, by exploiting the Whittle index (WI) theory, we rigorously establish the WI indexability and derive a scalable closed form solution. Consequently, in our WI policy, each user only needs to calculate its WI and report it to the BS, and the users with the highest indices are selected for task offloading. Furthermore, when the task completion ratio becomes the focus, the shorter slack time less remaining workload (STLW) priority rule is introduced into the WI policy for performance improvement. When the knowledge of user offloading energy consumption is not available prior to the offloading, we develop Bayesian learning-enabled WI policies, including maximum likelihood estimation, Bayesian learning with conjugate prior, and prior-swapping techniques. Simulation results show that the proposed policies significantly outperform the other existing policies.
Radiomics analysis of multiphase contrast-enhanced CT imaging for differentiating primary gastric lymphoma and Borrmann type IV gastric cancer
Authors: Liu Xia , Chen Xiao-li , Zhang Xin , Pu Hong , Li Hang 
Published: January 2024

Abstract
Clinical diagnosis of Borrmann type IV GC is highly challenging since it has many similar clinicopathologic features with PGL. Radiomics is a promising medical application that demonstrates image analysis may be improved by extracting and selecting a lot of imformation. Previous studies used texture-based or radiomics techniques to differentiate the two gastric malignancies. Nevertheless, radiomics features were extracted only from venous CT images rather than multiphase contrast-enhanced CT images. In the present study, Radiomics features were extracted from unenhanced phase, arterial phase, venous phase, double-phase(arterial + venous), three-phase (unenhanced + arterial + venous) CT images. As a result, we found Clinical model comprised of high-enhanced serosa sign, normalized CT value on venous phase, and perigastric fat infiltration showed good performance with an area under the ROC curve (AUC) of 0.902 and 0.878 in the training set and testing set. Compared with the other radiomics models, three-phase radiomics model showed better performance with AUC of 0.871 and 0.865 in the training set and testing set, respectively. The clinical-radiomics model further improved the discriminatory performance (AUC, 0.960) in the training set and testing set (AUC, 0.932). The DCA showed the highest benefit for clinical-radiomics model. Overall, this study shows that the combined clinical-radiomic model incorporating three-phase radiomics signatures and CT findings achieved a satisfactory performance in distinguishing PGL from Borrmann type IV GC.
Methodological Advances in Patient-centered Rare Disease Research: the UTHealth Houston Turner Syndrome Society of the United States Research Registry
Authors: Mansoorshahi Sara , Scurlock Cindy , Registry Scientific Advisory Board of the Turner Syndrome Research , Prakash Siddharth K. 
Published: January 2024

Abstract
Background: Many different clinical specialists provide care to patients with Turner syndrome (TS), who have highly variable clinical manifestations. Therefore, a national TS registry is essential to inform a cohesive approach to healthcare and research. In 2015, the Turner Syndrome Society of the United States (TSSUS) created the Turner Syndrome Research Registry (TSRR) to engage directly with community participants who voluntarily provide longitudinal data about their experiences with TS. TSRR projects are collaborative partnerships between people with TS, TSSUS, and researchers.
Results: To ensure that registry workflows conform to the data privacy choices of participants, TSSUS collaborated with UTHealth Houston in 2021 to create a new version of the TSRR that completely separates participant health data (stored at UTHealth) and personal identifiers (maintained at TSSUS). We developed an innovative Visual Basic (VB) script that, when embedded into Microsoft Outlook, redirects REDCap surveys through TSSUS to participants by matching registry IDs to participant email addresses. Additionally, the utilization of REDCap allows for portability of data as it is an open source platform.
Conclusion: In this report, we will highlight three recent changes that more closely align the TSRR with this mission: a unique and equal collaborative partnership between UTHealth and TSSUS, an open-source platform, REDCap, that ensures data portability and compatibility across institutions, and an innovative survey routing system that retains participant confidentiality without sacrificing REDCap survey distribution capabilities to connect researchers with thousands of participants.
Dual Release of Daptomycin and BMP-2 from a Composite of β-TCP Ceramic and ADA Gelatin for Bone Regeneration
Authors: Ritschl Lucas , Schilling Pia , Wittmer Annette , Serr Annerose , schmal hagen , Seidenstuecker Michael 
Published: January 2024

Abstract

Background
Antibiotic-containing carrier systems are one option that offers the advantage of releasing active ingredients over a longer period of time. In vitro sustained drug release from a carrier system consisting of microporous β-TCP ceramic and alginate has been reported in previous works. Alginate dialdehyde (ADA) gelatin gel showed both better mechanical properties when loaded into a β-TCP ceramic and higher biodegradability than pure alginate.
Methods
Dual release of daptomycin and BMP-2 was measured on days 1, 2, 3, 6, 9, 14, 21, and 28 by HPLC and ELISA. After release, the microbial efficacy of the daptomycin was verified and the biocompatibility of the composite was tested in cell culture.
Results
Daptomycin and the model compound FITC protein A (n = 30) were released from the composite over 28 days. A Daptomycin release above the minimum inhibitory concentration (MIC) by day 9 and a burst release of 71.7 ± 5.9% were observed in the loaded ceramics. Low concentrations of BMP-2 were released from the loaded ceramics over 28 days.
Physical properties and chemical composition of banana blossom sheaths with different skin colors and its application as a raw material for healthy pasteurized banana blossom juice
Authors: Jongrattanavit Kankanit , Pinkaew Panyapathk 
Published: January 2024

Abstract
The objectives of this research were to study the physical properties, chemical composition of banana blossom sheaths, and microbial quality of its juices. Banana blossom sheaths have different skin colors; the inner is light-yellow, and the outer is pink red. It was found that the light-yellow inner banana blossom sheaths were a source of protein (24.12 g/100 g of sample) and total phenolic compounds (13.58 mg of gallic acid equivalents (GAE)/g dry weight), and the pink-red outer sheaths of banana blossoms were a source of fibers (27.39 g/100 g of sample) and total anthocyanin content (6.43 mg). The healthy pasteurized banana blossom juices produced from the inner and the outer sheaths of banana blossoms are sources of phenolic compounds (254 and 124 mg GAE/100 mL), total anthocyanin contents (0.19 and 15.01 mg cyanidin-3-glucoside equivalent (CGE)/100 mL), and antioxidant properties using the DPPH method (2,280.49 and 2,156.53 µmol of Trolox equivalents/100 mL), respectively.