bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling of two-stage anaerobic onsite wastewater sanitation system to predict effluent soluble chemical oxygen demand through machine learning
Authors: Mathur Rajshree , Sharma Meena Kumari , Loganathan K. , Abbas Mohamed , Hussain Shaik , Kataria Gaurav , Alqahtani Mohammed S. , Srinivas Rao Koppula 
Published: January 2024

AbstractThe present research aims to predict effluent soluble chemical oxygen demand (SCOD) in anaerobic digestion (AD) process using machine-learning based approach. Anaerobic digestion is a highly sensitive process and depends upon several environmental and operational factors, such as temperature, flow, and load. Therefore, predicting output characteristics using modeling is important not only for process monitoring and control, but also to reduce the operating cost of the treatment plant. It is difficult to predict COD in a real time mode, so it is better to use Complex Mathematical Modeling (CMM) for simulating AD process and forecasting output parameters. Therefore, different Machine Learning algorithms, such as Linear Regression, Decision Tree, Random Forest and Artificial Neural Networks, have been used for predicting effluent SCOD using data acquired from in situ anaerobic wastewater treatment system. The result of the predicted data using different algorithms were compared with experimental data of anaerobic system. It was observed that the Artificial Neural Networks is the most effective simulation technique that correlated with the experimental data with the mean absolute percentage error of 10.63 and R2 score of 0.96. This research proposes an efficient and reliable integrated modeling method for early prediction of the water quality in wastewater treatment.
Improved target detection method for space-based optoelectronic systems
Authors: Zhu Rui , Fu Qiang , Liu Nan , Zhao Feng , Wen Guanyu , Li Yingchao , Jiang Huilin 
Published: January 2024

AbstractThe detection of faint and small targets by space-based surveillance systems is difficult owing to the long distances, low energies, high speeds, high false alarm rates, and low algorithmic efficiencies involved in the process. To improve space object detection and help prevent collisions with critical facilities such as satellites, this study proposes an improved method for the detection of faint and small space-based targets. The proposed method consists of two components: star atlas preprocessing and space-based target detection. The star atlas preprocessing step applies multi-exposure image pyramidal weighted fusion to the original image containing the faint and small space-based target. After obtaining the image pyramidal weighted fusion result atlas, the algorithm employs threshold segmentation to improve the overall image clarity, highlight image details, and provide additional information for target detection. The detection of targets partially relies on the local symmetry of the image. Accordingly, a diffusion function describing the local symmetry is established to precisely locate stars by measuring the symmetry factor in a small area surrounding each pixel in the star atlas. This effectively removes the background stars while retaining high-definition and high-contrast images. The efficacy of the algorithm is validated using simulated datasets consisting of space-based and real images. The results demonstrate that the proposed technique improves the applicability of the multistage hypothesis testing (MHT) method in the context of a complex space environment, thus improving the performance of the space-based electro-optical detection system to better catalogue, identify, and track space targets.
Ensemble learning based compressive strength prediction of concrete structures through real-time non-destructive testing
Authors: Arora Harish Chandra , Bhushan Bharat , Kumar Aman , Kumar Prashant , Hadzima-Nyarko Marijana , Radu Dorin , Cazacu Christiana Emilia , Kapoor Nishant Raj 
Published: January 2024

AbstractThis study conducts an extensive comparative analysis of computational intelligence approaches aimed at predicting the compressive strength (CS) of concrete, utilizing two non-destructive testing (NDT) methods: the rebound hammer (RH) and the ultrasonic pulse velocity (UPV) test. In the ensemble learning approach, the six most popular algorithms (Adaboost, CatBoost, gradient boosting tree (GBT), random forest (RF), stacking, and extreme gradient boosting (XGB)) have been used to develop the prediction models of CS of concrete based on NDT. The ML models have been developed using a total of 721 samples, of which 111 were cast in the laboratory, 134 were obtained from in-situ testing, and the other samples were gathered from the literature. Among the three categories of analytical models—RH models, UPV models, and combined RH and UPV models; seven, ten, and thirteen models have been used respectively. AdaBoost, CatBoost, GBT, RF, Stacking, and XGB models have been used to improve the accuracy and dependability of the analytical models. The RH-M5, UPV-M6, and C-M6 (combined UPV and RH model) models were found with highest performance level amongst all the analytical models. The MAPE value of XGB was observed to be 84.37%, 83.24%, 77.33%, 59.46%, and 81.08% lower than AdaBoost, CatBoost, GBT, RF, and stacking, respectively. The performance of XGB model has been found best than other soft computing techniques and existing traditional predictive models.
Atmospheric non-thermal plasma inactivation of Ascosphaera apis, the causative agent of chalkbrood disease in honeybee
Authors: Boonmee Thummanoon , Sinpoo Chainarong , Thayatham Kunlada , Suanpoot Pradoong , Disayathanoowat Terd , Pettis Jeffery S. , Chaimanee Veeranan 
Published: January 2024

AbstractAscosphaera apis is a worldwide pathogenic fungi of honeybees that can cause a decline in bee populations. In this study, we investigated the antifungal activity of non-thermal plasma on fungal growth. Spore inactivation after exposure to gas plasma by liquid phase and plasma activated water (PAW) and pathogenicity of A. apis in vivo were also examined. The results demonstrated that the mycelial growth of fungi was completely inhibited after argon plasma treatment. Both gas plasma and PAW exposures resulted in a significant decrease of A. apis spore numbers, maximum reduction of 1.71 and 3.18-fold, respectively. Germinated fungal spores on potato dextrose agar were also reduced after plasma treatment. SEM analysis revealed a disruption in the morphological structure of the fungal spores. The pathogenicity of A. apis on honeybee larvae was decreased after spores treated by gas plasma and PAW with a disease inhibition of 63.61 ± 7.28% and 58.27 ± 5.87%, respectively after 7 days of cultivation. Chalkbrood in honey bees have limited control options and our findings are encouraging. Here, we demonstrate a possible alternative control method using non-thermal plasma for chalkbrood disease in honeybees.
Effect of longer femoral head on leg length, offset, and range of motion in total hip arthroplasty: a simulation study
Authors: Shimizu Tomohiro , Miyazaki Takuji , Yokota Shunichi , Ishizu Hotaka , Takahashi Daisuke , Iwasaki Norimasa 
Published: January 2024

AbstractIn this study, we investigated the relationship between head length, leg length, offset, and dislocation resistance using range of motion (ROM) simulations based on computed tomography data to examine if a longer femoral head reduces the risk of dislocation. The femoral components were set to eliminate leg length differences with a + 0 mm head, and variations for + 4-, + 7-, and + 8-mm heads were analyzed. Offset and ROM were assessed when longer heads were used, with the leg length adjusted to be similar to that of the contralateral side. While internal rotation at flexion and external rotation at extension increased with + 4-mm longer heads, the + 7- and + 8-mm heads did not increase dislocation resistance. When adjusting for leg length, the longer heads showed no significant differences in offset and ROM. Enhancing dislocation resistance by solely increasing the offset with a longer head, while simultaneously adjusting the depth of stem insertion, may be a beneficial intraoperative technique. Although a + 4-mm longer head possibly increases ROM without impingement, heads extended by + 7 or + 8 mm may not exhibit the same advantage. Therefore, surgeons should consider this technique based on the implant design.
Rice residue management alternatives in rice–wheat cropping system: impact on wheat productivity, soil organic carbon, water and microbial dynamics
Authors: Korav Santosh , Yadav Dharam Bir , Yadav Ashok , Rajanna G. A. , Parshad Jagdish , Tallapragada Sridevi , Elansary Hosam O. , Mahmoud Eman A. 
Published: January 2024

AbstractIn the Indo-Gangetic Plains (IGP), rice–wheat cropping system (RWCS) predominates, producing large quantity of crop residue and its management is major concern. Farmers usually burn the residue to clear the field for succeding crop, and burning damages soil microbes, resulted in loss of soil organic matter. Hence, current study was conducted to assess the impact of different Happy seeder based residue management options on changes in microbial dynamics, enzyme activities and soil organic matter content and also to know that alternative method for attaining sustainable wheat productivity in sandy loam soils of Haryana, India. Results revealed that Zero tillage wheat (ZTW) with partial and full residue retention treatments sown with Happy seeder (after using chopper and spreader), and ZTW with anchored stubbles significantly enhanced soil microbial count by 47.9–60.4%, diazotropic count by 59.0–73.1% and actinomycetes count by 47.3–55.2%, grain yield by 9.8–11.3% and biomass yield by 7.4–9.6% over conventional tilled (CT) residue burning and residue removal plots. ZTW sown with surface retention of rice crop residue increased the organic carbon by 0.36–0.42% and the soil moisture content by 13.4–23.6% over CTW without residue load. Similarly, ZTW sown with Happy seeder with full residue enhanced alkaline phosphatase activity from 95.3 µg TPF g−1 soil 24 h−1 in 2018–2019 to 98.6 µg TPF g−1 soil 24 h−1 in 2019–2020 over control plots. Likely, microbial population and enzymatic activity showed strong positive correlation under variable residue retention practices. However, increased microbial population reduced the soil pH from 7.49 to 7.27 under ZTW with residue retention plots. The wheat yield enhanced by 9.8–11.3% during 2018–2019 and 2019–2020 under ZTW with Happy seeder with full residue load over residue burning and residue removal plots. ZTW sown with Happy seeder under full residue retention, achieved maximum net return 43.16–57.08 × 103 ₹ ha−1) and B-C ratio (1.52 to 1.70) over CTW without residue. Therefore, rice residue needs to be managed by planting wheat using appropriate machinery under ZT for sustaining higher productivity in RWCS and improve soil health and environment under IGP regions.
Effect of polyp regression and reduction on treatment efficacy in polypoidal choroidal vasculopathy treated with aflibercept
Authors: Sayanagi Kaori , Fujimoto Satoko , Hara Chikako , Fukushima Yoko , Maruyama Kazuichi , Kawasaki Ryo , Sato Shigeru , Nishida Kohji 
Published: January 2024

AbstractIntravitreal injection of aflibercept (IVA) has successfully treated polypoidal choroidal vasculopathy (PCV), and polyp morphology is an important indicator of treatment efficacy. However, many studies have not reported the presence or absence of polyp regression and treatment outcomes, and few studies have reported polyp reduction and treatment outcomes in cases with residual polyps. We retrospectively measured the polyp area on indocyanine green angiography images before and after the IVA loading phase and investigated the regression and reduction of polyps and treatment outcomes of 81 eyes with PCV treated with IVA. We investigated the relationship between the presence or absence of complete regression of polyps and the percentage change in the polyp area and treatment outcomes. Eyes with complete polyp regression had significantly better visual acuity improvements compared with baseline at 12 months (P = 0.0108), fewer treatments (P = 0.0024), fewer recurrences during 12-months follow-up (P = 0.0010), and more “dry maculas” at 3 months (P = 0.0048) than eyes in which polyp regression did not occur. A significant correlation was seen only between the percentage of polyp regression and visual acuity at 3 months (P = 0.0395). Regarding IVA therapy for PCV, the presence or absence of complete polyp regression at the end of the loading phase affected the treatment outcome, whereas the degree of polyp reduction in cases of residual polyps had no effect.
Effects of Enterococcus faecium (R8a) on nonspecific immune gene expression, immunity and intestinal flora of giant tiger shrimp (Penaeus monodon)
Authors: Sun Xueliang , Fang Zhenzhen , Yu Hong , Zhao Honghao , Wang Yang , Zhou Falin , Zhao Lin , Sun Jingfeng , Tian Yunchen 
Published: January 2024

AbstractIn this study, Penaeus monodon were gave basic feed supplemented with three levels of Enterococcus faecium. Then, the expression of non-specific immunity-related genes, and the activities of total antioxidant capacity (T-AOC), superoxide dismutase (SOD), malondialdehyde (MDA), acid phosphatase (ACP), alkaline phosphatase (AKP), phenol oxidase (PO) were evaluated. Meanwhile, the disease resistance test and intestinal flora determination were conducted. The results showed that the MDA levels of 2% and 5% E. faecium groups were significantly lower than that of the control group (P < 0.05). While the SOD and T-AOC and ACP and AKP of experimental groups were significantly higher (P < 0.05), the PO of experimental groups were significantly lower than that of the control group (P < 0.05). In addition, the expressions of immunity-related genes (tlr22, dorsal, lysozyme, crustin, imd, and relish) in the 2% and 5% E. faecalis groups were significantly greater than those in the control group (P < 0.05). After P. monodon was challenged with Vibrio parahaemolyticus for 7 days, the average cumulative mortality of P. monodon in the 2% and 5% groups were significantly lower than that in the 0% group (P < 0.05). With the increase of feeding time, the number of effective OTUs in each group showed a downward trend. At the 14th d, Proteobacteria, Bacteroidetes and Firmicutes, the dominant flora in the intestinal tract of P. monodon. In summary, supplied with E. faecium could increase the expression of non-specific immunity-related genes, enhance the immune capacity of P. monodon.
Retraction Note: Where Do Deceased Children Go? A Spiritual View
Authors: Çaksen Hüseyin 
Published: January 2024

RetractionAn investigation by the publisher found a number of articles, including this one, published in Journal of Child Science in Volume 12, Number 01, e146–e147, on October 07, 2022 (DOI: 10.1055/s-0042-1757145), with a number of concerns, including but not limited to undeclared conflicts of interest and manipulated peer review procedures. As a result, the publisher has retracted and removed this article.
Soil seed bank dynamics of two invasive alien plants in Nigeria: implications for ecosystem restoration
Authors: Akomolafe Gbenga F , Rosazlina Rusly , Omomoh Bernard 
Published: January 2024

Abstract
The assessment of seed banks could provide useful hints towards ensuring restoration planning and invasive species management. In this study, the impacts of two invaders such as Hyptis suaveolens and Urena lobata on the soil seed banks were investigated. We also assessed the seed characteristics of the invaders at the invaded sites. This was achieved using 10 sites each for H. suaveolens- and U. lobata-invaded habitats and -non-invaded habitats making a total of 30 sites. We collected 200 soil samples from each habitat type. A seedling emergence method was used to determine the seed bank recruitment of both invasive plants. The diversity indices of the above-ground vegetation of sites invaded by the two plants were significantly lower than those of the non-invaded sites. Only two plant species emerged from the seed banks of H. suaveolens and five plants from those of U. lobata when compared with non-invaded sites where 53 species emerged. A larger portion of the seeds was located in the soil’s lower layer at all the sites invaded by H. suaveolens while those of U. lobata and non-invaded sites were found in the upper layers and there are significant associations between the habitats. The lower soil layers of the two species have the highest percentage of viable seeds. These results help us to understand more about the invasiveness of both species as related to their impacts on the seed banks and native vegetation. It also indicates that the native species that emerged from the invaded seed banks could be used for the restoration of the invaded habitats.
SL-Miner: a web server for mining evidence and prioritization of cancer-specific synthetic lethality
Authors: Liu Xin , Hu Jieni , Zheng Jie 
Published: January 2024

Abstract

Summary
Synthetic lethality (SL) refers to a type of genetic interaction in which the simultaneous inactivation of two genes leads to cell death, while the inactivation of a single gene does not affect cell viability. It significantly expands the range of potential therapeutic targets for anti-cancer treatments. SL interactions are primarily identified through experimental screening and computational prediction. Although various computational methods have been proposed, they tend to ignore providing evidence to support their predictions of SL. Besides, they are rarely user-friendly for biologists who likely have limited programming skills. Moreover, the genetic context specificity of SL interactions is often not taken into consideration. Here, we introduce a web server called SL-Miner, which is designed to mine the evidence of SL relationships between a primary gene and a few candidate SL partner genes in a specific type of cancer, and to prioritize these candidate genes by integrating various types of evidence. For intuitive data visualization, SL-Miner provides a range of charts (e.g. volcano plot and box plot) to help users get insights from the data.

Availability and implementation
SL-Miner is available at https://slminer.sist.shanghaitech.edu.cn.
QATS: an ImageJ plugin for the quantification of toroidal nuclei in biological images
Authors: Pons Carles , Mauvezin Caroline 
Published: January 2024

Abstract

Motivation
The toroidal nucleus is a novel chromosomal instability (CIN) biomarker which complements the micronucleus. Understanding the specific biological stresses leading to the formation of each CIN-associated phenotype requires the evaluation of large panels of biological images collected from different genetic backgrounds and environmental conditions. However, the quantification of toroidal nuclei is currently a manual process which is unviable on a large scale.

Results
Here, we present QATS (QuAntification of Toroidal nuclei in biological imageS), a tool that automates the identification of toroidal nuclei, minimizing false positives while highly agreeing with the manual quantifications. Additionally, QATS identifies micronuclei for a convenient comparison of both CIN biomarkers. QATS is an open-source ImageJ plugin with a user-friendly interface that enables a wide scientific community to easily assess the frequency of CIN biomarkers for the determination of CIN levels in cellular models.

Availability and implementation
QATS is an ImageJ plugin freely available at http://www.toroidalnucleus.org/qats. The user manual and the images used for the evaluation of QATS are included in the website. Supplementary data are available at Bioinformatics online.
Conumee 2.0: enhanced copy-number variation analysis from DNA methylation arrays for humans and mice
Authors: Daenekas Bjarne , Pérez Eilís , Boniolo Fabio , Stefan Sabina , Benfatto Salvatore , Sill Martin , Sturm Dominik , Jones David T W , Capper David , Zapatka Marc , Hovestadt Volker 
Published: January 2024

Abstract

Motivation
Copy-number variations (CNVs) are common genetic alterations in cancer and their detection may impact tumor classification and therapeutic decisions. However, detection of clinically relevant large and focal CNVs remains challenging when sample material or resources are limited. This has motivated us to create a software tool to infer CNVs from DNA methylation arrays which are often generated as part of clinical routines and in research settings.

Results
We present our R package, conumee 2.0, that combines tangent normalization, an adjustable genomic binning heuristic, and weighted circular binary segmentation to utilize DNA methylation arrays for CNV analysis and mitigate technical biases and batch effects. Segmentation results were validated in a lung squamous cell carcinoma dataset from TCGA (n = 367 samples) by comparison to segmentations derived from genotyping arrays (Pearson’s correlation coefficient of 0.91). We further introduce a segmented block bootstrapping approach to detect focal alternations that achieved 60.9% sensitivity and 98.6% specificity for deletions affecting CDKN2A/B (60.0% and 96.9% for RB1, respectively) in a low-grade glioma cohort from TCGA (n = 239 samples). Finally, our tool provides functionality to detect and summarize CNVs across large sample cohorts.

Availability and implementation
Conumee 2.0 is available under open-source license at: https://github.com/hovestadtlab/conumee2.
Insights into the inner workings of transformer models for protein function prediction
Authors: Wenzel Markus , Grüner Erik , Strodthoff Nils 
Published: January 2024

AbstractMotivationWe explored how explainable artificial intelligence (XAI) can help to shed light into the inner workings of neural networks for protein function prediction, by extending the widely used XAI method of integrated gradients such that latent representations inside of transformer models, which were finetuned to Gene Ontology term and Enzyme Commission number prediction, can be inspected too.ResultsThe approach enabled us to identify amino acids in the sequences that the transformers pay particular attention to, and to show that these relevant sequence parts reflect expectations from biology and chemistry, both in the embedding layer and inside of the model, where we identified transformer heads with a statistically significant correspondence of attribution maps with ground truth sequence annotations (e.g. transmembrane regions, active sites) across many proteins.Availability and ImplementationSource code can be accessed at https://github.com/markuswenzel/xai-proteins.