bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nitrogen Management for Optimum Potato Yields and Low Environmental Impact in Northwest China
Authors: Yang Haibo , Di Yunfei , Zhang Hailin , Li Fei 
Published: September 2023

Abstract
Understanding the changes in nitrate nitrogen (NO3−-N) content in the rooting zone is crucial for reducing nitrate leaching and improving nitrogen (N) use efficiency. The main objective of this study was to investigate the effects of N management strategies on NO3−-N dynamics in the main root zone (0–60 cm) at critical growth stages of drip-irrigated potatoes and to quantify the retention capacity of NO3−-N at harvest in an intensive potato cropping system. Three field experiments with no N application (CK), optimized management (OM) based on a realistic yield goal and soil mineral N content (Nmin) and farmer practice (FP) for three potato cultivars were conducted in Inner Mongolia of Northwest China from 2014 to 2016. A total of 52 farmers with over 3000 hectares of potato fields were also investigated at harvest. The results showed that OM treatment improved N use efficiency and reduced the environmental risk of N loss while ensuring potato yields. Overusing N fertilizer in farmer fields was common, but these N fertilizers only caused a temporary accumulation of NO3−-N during the growing season, then was reduced to the same level as the optimal treatment at harvest. The NO3−-N retention was about 70 kg ha− 1 at harvest in the drip-irrigated potatoes with higher yield and the data from farmers’ fields confirmed the universality of the NO3−-N retention content. Although retentional NO3−-N content in the main root zone at harvest was similar between FP and OM, over-application of N and additional leaching loss from FP were observed. The characteristics of soil NO3−-N accumulation in the root zone of drip-irrigated potatoes help to improve management strategies to maximize potato yield while minimizing environmental risks due to N fertilization.
Deep Learning based Automatic Image Annotation System for Image Retrieval with Arabic language
Authors: Al-Shammary Ali Abbas , Zaghden Nizar , Bouhlel Med Salim 
Published: September 2023

Abstract
Social media platforms like YouTube, Twitter, and Facebook have grown into new modalities of communication, allowing a great number of individuals to interact and learn. Furthermore, many social media users currently produce and share incorrect thoughts and images that are not accompanied by words. The automated generation of any text for raw photos is a difficult operation, particularly when working with Arabic and a limited amount of training samples. To tackle this challenge, smart technology and deep learning technology have been offered. The method employs a bi-level architecture, which allows for the use of self-supervision to produce rotation variants in order to increase the number of training samples. This, in turn, enhances the variability of the model representation and enables the investigation of high-level object information for more detailed picture production. GoogleNet model automatically overcomes the stability issues associated with parsing and synthesising any picture. The proposed technique makes use of deep learning technology to explain images received from the internet environment and gather information about the existence of identified items in order to create an optimal detection method that does not interfere with the deep learning process.
Impact of HER2-low status for patients with early-stage breast cancer and non-pCR after neoadjuvant chemotherapy: A National Cancer Database Analysis
Authors: Li Huiyue , Plichta Jennifer K. , Li Kan , Jin Yizi , Thomas Samantha M. , Ma Fei , Tang Li , Wei Qingyi , He You-Wen , Chen Qichen , Guo Yuanyuan , Liu Yueping , Zhang Jian , Luo Sheng 
Published: September 2023

Abstract
Purpose
To investigate potential differences in pathological complete response (pCR) rates and overall survival (OS) between HER2-low and HER2-zero patients with early-stage hormone receptor (HR)-positive and triple-negative breast cancer (TNBC), in the neoadjuvant chemotherapy setting.
Methods
We identified early-stage invasive HER2-negative BC patients who received neoadjuvant chemotherapy diagnosed between 2010 and 2018 in the National Cancer Database. HER2-low was defined by immunohistochemistry (IHC) 1 + or 2 + with negative in-situ hybridization, and HER2-zero by IHC0. All the methods were applied separately in the HR-positive and TNBC cohorts. Logistic regression was used to estimate the association of HER2 status with pCR (i.e., ypT0/Tis and ypN0). Kaplan-Meier method and Cox proportional hazards model were applied to estimate the association of HER2 status with OS. Inverse probability weighting and/or multivariable regression were applied to all analyses.
Results
For HR-positive patients, 70.9% (n = 17,934) were HER2-low, whereas 51.1% (n = 10,238) of TNBC patients were HER2-low. For both HR-positive and TNBC cohorts, HER2-low status was significantly associated with lower pCR rates [HR-positive: 5.0% vs. 6.7%; weighted odds ratio (OR) = 0.81 (95% CI: 0.72–0.91), P < 0.001; TNBC: 21.6% vs. 24.4%; weighted OR = 0.91 (95% CI: 0.85–0.98), P = 0.007] and improved OS [HR-positive: weighted hazard ratio = 0.85 (95% CI: 0.79–0.91), P < 0.001; TNBC: weighted hazard ratio = 0.91 (95% CI: 0.86–0.96), P < 0.001]. HER2-low status was associated with favorable OS among patients not achieving pCR [HR-positive: adjusted hazard ratio = 0.83 (95% CI: 0.77–0.89), P < 0.001; TNBC: adjusted hazard ratio = 0.88 (95% CI 0.83–0.94), P < 0.001], while no significant difference in OS was observed in patients who achieved pCR [HR-positive: adjusted hazard ratio = 1.00 (95% CI: 0.61–1.63), P > 0.99; TNBC: adjusted hazard ratio = 1.11 (95% CI: 0.85–1.45), P = 0.44].
Conclusion
In both early-stage HR-positive and TNBC patients, HER2-low status was associated with lower pCR rates. HER2-zero status might be considered an adverse prognostic factor for OS in patients not achieving pCR.
Safety Netting Advice for Acutely Ill Children Presenting to Ambulatory Care: Exploring Parents’ Opinions, Ideas, and Expectations Through Focus Group Interviews
Authors: Burvenich Ruben , Heytens Stefan , Bos David AG , Roy Kaatje Van , Struyf Thomas , Toelen Jaan , De Sutter An , Verbakel Jan Y 
Published: September 2023

Abstract
Background. Safety netting advice is an essential component of the management of acutely ill children, yet an international consensus definition is lacking. More research on parents’ ideas about safety netting advice is needed to develop a broadly supported definition. In this study we aimed to explore the perspectives of Belgian parents about safety netting advice for their acutely ill child(ren) presenting to ambulatory care.Methods . We conducted focus groups with Belgian parents of children 6 months to 12 years old who were recruited through maximum variation sampling. We transcribed the interviews verbatim. Using a combination of inductive and deductive ‘in vivo’ coding we distilled themes from the data. As per the Grounded Theory approach, we reiterated between data collection, coding, and analysis. After participant validation of provisional themes, we constructed the final thematic framework.Results. Through six focus groups with 30 parents, we identified five themes: (1) Relevant background information; (2) To know what to expect, what to look out for; (3) Instructions on child homecare and when to revisit a physician; (4) Physicians who consider parents’ perspectives and contexts; (5) A reliable source that provides safety netting advice only when necessary, possibly in a multimodal way.Conclusions. Our findings highlight the importance of clear and tailored background information and instructions from a reliable source on what to expect and what to look out for and what to do next when the child’s situation worsens. Our results can serve as an evidence base for further research into defining safety netting advice.
Investigation Diagnostic Gene Markers and Immune Infiltration in Idiopathic Pulmonary Fibrosis
Authors: sun shuang , Zhong diansheng 
Published: September 2023

Abstract
Objective: Idiopathic pulmonary fibrosis (IPF) is a difficult to cure and low survival lung disease, and the pathogenesis has not been elucidated clearly. This study is to explore the potential hub genes in IPF and explore their role in the progression of IPF with immune cell infiltration, providing evidence support for potential diagnostic markers and targets of IPF.
Method: Download the dataset GSE10667 from the GEO database to identify differentially expressed genes (DEG) between IPF patients and the normal population. Exploring hub genes related to IPF using differential expression analysis and Weighted correlation network analysis (WGCNA). Establish a Nomogram model and ROC (Receiver Operating Characteristic) curve to evaluate the diagnostic effectiveness of hub genes. Apply Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway-based enrichment analysis to explore the potential roles of these hub genes. Discover key networks of genes in protein level by Protein-Protein Interaction Networks (PPI) networks. And investigate the relationship between key gene MMP2(metallopeptidase 2) and immune infiltration. Finally, based on Genome-wide association study (GWAS), a Mendelian randomization study was conducted to determine the causal relationship between MMP2 and IPF.
Result:A total of 486 DEGs were identified in IPF patients. Gene co expression network was established by WGCNA to screen the highest correlation module. And The genes in it were mainly enriched in extracellular matrix （ECM ）formation, cell aging, endoplasmic reticulum stress, and metalloproteinase activation signaling pathways. Cross the genes in the DEG related modules with WGCNA traits to obtain the core hub genes. Then, key genes COL1A1, COL3A1, COL1A2, POSTN, MMP2 were found through the PPI. The nomogram was established to verify the risk of disease occurrence, and the ROC was applied to demonstrate the accuracy of the model and shows that five hub genes are potential biomarkers for IPF. Finally, we selected MMP2 and found a causal relationship with the occurrence and prognosis of IPF through Mendelian randomization (MR)studies, as well as immune cell infiltration in IPF.
Conclusion: We have identified the pivot gene MMP2 associated with IPF, which may play a key role in the progression of IPF. And may play an significant role in the pre symptom diagnosis of IPF, providing new therapeutic targets, and predicting prognosis.
Variable-length Differential Evolution for Numerical and Discrete Association Rule Mining
Authors: Mlakar Uroš , Fister Iztok , Fister Iztok 
Published: September 2023

Abstract
This paper proposes a variable-length Differential Evolution for Association Rule Mining. The proposed algorithm includes a novel representation of individuals, which can encode both numerical and discrete attributes in their original or absolute complement of the original intervals. The fitness function used is comprised of a weighted sum of Support and Confidence Association Rule Mining metrics. The proposed algorithm was tested on fourteen publicly available, and commonly used datasets from the UC Irvine Machine Learning Repository. It is also compared to the nature inspired algorithms taken from the NiaARM framework, providing superior results. The implementation of the proposed algorithm follows the principles of Green Artificial Intelligence, where a smaller computational load is required for obtaining promising results, and thus lowering the carbon footprint.
Evaluation of clustering-based differential expression analysis methods for RNA-seq data
Authors: Makino Manon , Shimizu Kentaro , Kadota Koji 
Published: September 2023

Abstract
Background
RNA-seq is a tool for measuring gene expression and is commonly used to identify differentially expressed genes (DEGs). Gene clustering has been widely used to classify DEGs with similar expression patterns, but rarely used to identify DEGs themselves. We recently reported that the clustering-based method (called MBCdeg) for identifying DEGs has great potential. However, a thorough investigation of its feasibility is still needed.
Results
We compared a total of six competing methods: three conventional R packages (edgeR, DESeq2, and TCC) and three versions of MBCdeg (denoted as MBCdeg1, 2, and 3) corresponding to three different normalization algorithms. Different scenarios of simulated data generated from three R packages (TCC, compcodeR, and PROPER) were mainly evaluated based on the area under the receiver operating characteristic curve (AUC) as a measure for both sensitivity and specificity. We found that the modified version of MBCdeg2 performed well for many scenarios on simulated data. However, MBCdeg showed very unstable results between trials for identical real data.
Conclusions
The current MBCdeg2 shows excellent performance in simulation analysis, but not at a practical level for real data. Since further improvements are needed for MBCdeg to reach a practical level, we cannot recommend the use of the current MBCdeg. Our report suggests not only the need for method developers to carefully describe their shortcomings, but also the need for the reader to critically decipher the conclusions reached under what conditions.
A Comparative Analysis of Using Ensemble Trees for Botnet Detection and Classification in IoT
Authors: Saied Mohamed , GUIRGUIS SHAWKAT , Madbouly Magda 
Published: September 2023

Abstract
Enhancing IoT security is a corner stone for building trust in its technology and driving its growth. Limited resources and diversified nature of IoT devices make them vulnerable to attacks. Botnet attacks compromise the IoT systems and can pose significant security challenges. Numerous investigations have utilized machine learning and deep learning techniques to identify botnet attacks in IoT. However, achieving high detection accuracy with reasonable computational requirements is still a challenging research considering the particularity of IoT. This paper aims to analytically study the performance of the tree based machine learning in detecting botnet attacks for IoT ecosystems. Through an empirical study performed on a public botnet dataset of IoT environment, basic decision tree algorithm in addition to ensemble learning of different bagging and boosting algorithms are compared. The comparison covers two perspectives: IoT botnet detection capability and computational performance. Results demonstrated that the significant potential for the tree based ML algorithms in detecting network intrusions in IoT environments. The RF algorithm achieved the best performance for multi-class classification with accuracy rates of 0.999991 respectively. It achieved also the highest results in all other measures.
Highly sensitive acetone gas sensor based on gold nanoparticles modified W18O49 porous polymeric spheres
Authors: Zhang Ke , Zhu Pengdang , Li Yunsheng , Wei Hang , Zhang Ruiyu 
Published: September 2023

Abstract
A two-step solvothermal approach was used to create porous polymeric spheres of W18O49 modified with gold nanoparticles. Various characterizations of the material were carried out by XRD, SEM, etc., and the results show that the material is highly crystalline and the surface has a porous nature, in addition, the addition of gold substantially improves the adsorbed oxygen content. The results of the gas sensitivity test showed that the gold nanoparticle-modified W18O49 porous polymeric spheres showed a significant improvement in performance compared to pure W18O49. The gold nanoparticle-modified W18O49 porous polymeric spheres demonstrated an increased reaction value to 100 ppm acetone at a lower temperature of 220 °C (S=66, 2.57 times that of the pure material), a quick response/recovery time (5s/12s), as well as strong selectivity and stability. W18O49 porous polymeric spheres enhanced with gold nanoparticles have good potential for acetone gas detection and are likely to be used in high-performance sensors.
The mRNA content of plasma extracellular vesicles provides a window into the brain during cerebral malaria disease progression
Authors: Abdi Abdirahman , Mwikali Kioko , Mwangi Shaban , Pance Alena , Ochola-Oyier Lynette , Kariuki Symon , Newton Charles , Bejon Philip , Rayner Julian 
Published: September 2023

Abstract
The impact of cerebral malaria on the transcriptional profiles of cerebral tissue is difficult to study using non-invasive approaches. We isolated plasma extracellular vesicles (EVs) from patients with cerebral malaria and community controls and sequenced their RNA content. Deconvolution of the tissue origins of the EV-RNA revealed that EVs from cerebral malaria patients are predominantly enriched in transcripts of brain origin. Next, we used manifold learning on the EV-RNAseq data to determine pseudotime against the community control samples as the baseline reference. We found that neuronal transcripts in plasma EVs decreased as pseudotime progressed, while transcripts of glial, endothelial, and immune cell origins increased over pseudotime. Pseudotime was associated with clinicopathological parameters of disease severity, including retinopathy, metabolic acidosis, respiratory rate, anaemia, malnutrition, depth of unconsciousness and death. Plasma EVs further provided evidence of platelet activation, TNF signalling, neurotrophin signalling, long-term potentiation and glutamatergic signalling during late disease stages of cerebral malaria. The transcriptional responses of cerebral tissue in cerebral malaria can be studied non-invasively using EVs circulating in peripheral blood.
How common is otogenic meningitis? A retrospective study in southern Sweden over 18 years
Authors: Bjar Nora , Hermansson Ann , Gisselsson-Solen Marie 
Published: September 2023

Abstract
Background
Bacterial meningitis is a rare, but life-threatening disease, which sometimes occurs as a complication to acute otitis media (AOM). The proportion of meningitis cases originating from AOM is not clear.
Purpose
The aim of this study was to investigate the proportion of meningitis cases caused by AOM, to compare risk factors, bacteriology and outcome between otogenic and non-otogenic meningitis, and to analyse the incidence of bacterial meningitis after the introduction of conjugate pneumococcal vaccines (PCV).
Methods
The medical charts of all patients admitted to hospitals in southern Sweden with bacterial meningitis between 2000 and 2017 were retrieved. Based on otoscopy and/or imaging, the proportion of otogenic meningitis cases was calculated, as were annual incidences.
Results
A total of 216 patients were identified, 25 of whom died. The proportion of otogenic meningitis was 31% but varied from 6% among teenagers to 40% among adults. Before PCV, 23% of meningitis cases were children < 2 years, compared to 1% post-PCV. The average incidence in the adult population, on the other hand, increased post-PCV, though there were large annual variations. S. pneumoniae was the most commonly identified pathogen in everyone but teenagers, in whom N. meningitidis was predominant.
Conclusion
AOM is an important cause of meningitis in children and adults. Though bacterial meningitis almost disappeared in children < 2 years after the introduction of PCV, the incidence of pneumococcal meningitis in adults seems to have increased.
Enhancing Wheat (Triticum aestivum L.) Crop Yield and Water Use Efficiency: A Study on Canopy Air Temperature Difference-Based Drip Irrigation Scheduling in a Semi-Arid Region of Western India
Authors: Patel R. J. , Rank P. H. , Vekariya P. B. , Rank H. D. , Vadar H. R. , Parmar H. V. , Tiwari M. K. , Marviya P. B. , Lunagaria M. M. 
Published: September 2023

Abstract
This study addresses efficient water usage in wheat cultivation in a semi-arid region of India with clay loam soil and an increasing water supply-demand gap. It focuses on optimizing drip irrigation (DI) scheduling, of wheat crops, based on canopy air temperature difference (CATD) using the crop water stress index (CWSI). The field experiments were conducted for two winter seasons, employing high-discharge drip irrigation (DI) on wheat crop (variety - GW 366) at Junagadh Agricultural University (JAU), Gujarat, India. The experiment had nine treatments, each replicated three times in randomized blocks. The DI treatments labeled as T1 to T6, were irrigated at CATD values of -4, -3, -2, -1, 0, and 1 °C, respectively.. While T7 were irrigated by border irrigation. In order to define upper and lower baselines of CWSI, well watered treatments (T8) and extreme dry treatment (T9) DI were considered. The drip irrigation system (DIS) had an application rate of 7.78 mm/h with a uniformity coefficient of 90.40%. Compared to surface irrigation, DI resulted in water savings ranging from 3.52% (T1) to 43.24% (T6). Using real-time CATD data, the theoretical CWSI (CWSITh) and the vapor pressure deficit (VPD) based semi-empirical CWSI (CWSIVPD) were calculated as 0.3351 and 0.3668, respectively. CATD values showed significant variation in CWSI across treatments. The CWSI demonstrated sensitivity to water stress during critical growth stages. The study identified an optimal CATD of -1 °C, yielding 36.48% higher crop yield (4744 kg/ha), 30.23% water savings (388.42 mm), and notable 95.67% more water use efficiency (12.21 kg/ha-mm,), surpassing the outcomes of border irrigation (3476 kg/ha, 556.74 mm and 6.24 kg/ha-mm). These findings hold significant implications for farmers and policymakers, effectively addressing food and water security concerns. The study underscores the efficiency of DI combined with CATD-based irrigation scheduling in optimizing wheat crop performance. In the context of critical water management, this research provides essential insights for sustainable agricultural practices.
Unpredictable, sudden-onset bleeding in deer mice (Peromyscus maniculatus bairdii) after oral exposure to a gut-sterilising antibiotic cocktail
Authors: Stoppel Heike , Harvey Brian , Minnaar Nico , Venter Kobus , Bester Cor , Wolmarans De Wet 
Published: September 2023

Abstract
Background: Animal models are valuable tools to investigate contributions of the gut microbiota to human disorders. Deer mice are studied for their expression of obsessive-compulsive-like behaviour, which has recently been associated with gut dysbiosis in this model. To this end, sterilisation of the gut microbiota by means of orally administered antibiotic cocktails, is a common procedure when studying the pathological role of dysbiosis.
Methods: In this case report, we refer to six unexpected mortalities after exposing 26 adult deer mice (Peromyscus maniculatus bairdii) of both sexes to a gut sterilising regimen that consisted of ampicillin, vancomycin, imipenem, gentamycin, and amphotericin B.
Results and conclusion: We recorded fatal bleeding episodes in four male and two female mice. While vancomycin is suspected to be the main agent of concern, future studies are needed to divulge the underlying mechanisms that resulted in the reported deaths.