bluuebunny/crossref_metadata_2025_split huggingface dataset:
A national-level study on groundwater potentiality mapping using a hybrid machine learning models under the scenario of climate change
Authors: Sarkar Showmitra Kumar , Alshehri Fahad , . Shahfahad , Rahman Atiqur , Pradhan Biswajeet , mohamed ahmed 
Published: July 2022

Abstract
A severe threat to natural resources and human livelihood is groundwater scarcity. Therefore, mapping groundwater potentiality (GWP) is necessary for future resource management. In this article, a framework for conducting ensemble modeling is introduced. This framework will be used to map GWP at the national level under the climate change scenario. Thirteen elements linked to topography, geology, hydrology, and land cover, as well as six climatic indicators based on historical time series data, were used to map the GWP. To provide extremely reliable groundwater potentiality mapping, three traditional standalone machine learning techniques such as logistic model tree (LMT), logistic regression (LR), and artificial neural network (ANN) have been merged with a stacking ensemble framework. Using the empirical and binormal receiver operating characteristic curves, the GWP mapping has been validated (ROC curve). According to research, Bangladesh's major rivers run along the high GWP zones in the country's southern and central regions. Additionally, the validation using the ROC curve demonstrates that the stacking model which had all three MLAs—performed better than other models (AUC: 0.971). The study may have a substantial impact on Bangladesh's national water planning and policy, which will be made using evidence. Additionally, the suggested method might be applied to map GWP on a broader scale in additional nations as well as at the continental level.
Steering the Drug Release of Smart Magnetic Self-Assembled Nano Micelles in an Internal Thoracic Artery Flow for Breast Cancer Therapy
Authors: Sulttan Saad , Rohani Sohrab 
Published: July 2022

Abstract
Magnetic drug targeting (MDT) is one of the most modern techniques in cancer therapy for its ability to reduce the side effects of chemotherapy experienced by systemic administration. In this study, a comprehensive mathematical model has been developed to predict the drug particle trajectories of anticancer dasatinib magnetic nanomicelles (DAS-MNM) released in an internal thoracic artery (ITA) blood flow for breast cancer therapy. Several factors are investigated in regard to the efficiency of MDT through the ITA, including magnetic field strength (MFS), relative magnetic permeability, magnet size, drug particle size, and, initial position of drug particle. The drug particle trajectory results confirmed the successful MDT using an external magnetic field with a capture efficiency of more than 90%, through the accumulation of a wide range of particle sizes of DAS-MNM close to the external magnetic field source at the arterial wall than in other positions. Moreover, the results showed that the number of trapped particles increased with increasing both MFS and drug particle diameter within the target tissue, while the drug particle permeability does not have a considerable effect on the particle retention. In addition, for achieving a successful drug/cargo delivery through the arteries, the magnetic field, the particle size, and initial release locations should be adjusted simultaneously. The present work offers insights into the critical factors in MDT with a significant impact on breast cancer therapy, tissue engineering, and regenerative medicine.
Association of adherence to long-acting inhaler use for initial treatment of chronic obstructive pulmonary disease and acute exacerbation: A retrospective cohort study
Authors: Suh Hee-Sook , Chang Min-Seok , Yu Iseul , Park Sunmin , Lee Ji-Ho , Lee Seok Jeong , Lee Won-Yeon , Yong Suk Joong , Kim Sang-Ha 
Published: July 2022

Abstract
Background
This study aimed to determine the effect of long-acting inhaler medication use adherence on acute exacerbations in treatment-naïve patients with chronic obstructive pulmonary disease (COPD) from healthcare claim data.
Methods
Using the Korean Health Insurance Review and Assessment Service database from July 2015 to December 2016, patients with COPD aged ≥ 40 who had started using long-acting inhalers were enrolled and observed for 6 months. Patients who were prescribed long-acting inhalers and had been hospitalized or visited emergency department (ED) for COPD 6 months before the first prescription were excluded. Medication adherence was indirectly measured by the medication possession ratio (MPR) based on the adherence (MPR ≥ 80%) and non-adherence (MPR < 80%) groups.
Results
A total of 3,959 patients were enrolled: 60.4% and 39.6% in the adherence and non-adherence groups, respectively. The risk factor analysis showed that the relative risk of acute exacerbation in the non-adherence group was 1.58 (95% confidence interval [CI] 1.25 − 1.99) in comparison to the adherence group. The logistic regression analysis after adjustment for patient-related variables demonstrated that the relative risk of acute exacerbation in the non-adherence group vs. the adherence group was 1.68 (95% CI 1.32 − 2.14) in terms of the number of inhalers used. Good adherence positively influenced the decreased rate in acute exacerbation for patients with COPD.
Conclusions
The risk of acute exacerbation of COPD requiring hospitalization or ED visit was low in the long-acting inhaler adherence group, suggesting that medication adherence imposes a reduction effect on acute exacerbation even in the initial management among treatment-naïve patients.
An archaeal compound as a driver of Parkinson’s disease pathogenesis
Authors: Wilmes Paul , Trezzi Jean-Pierre , Aho Velma , Jäger Christian , Schade Sebastian , Janzen Annette , Hickl Oskar , Kunath Benoit , Thomas Mélanie , Schmit Kristopher , Garcia Pierre , Sciortino Alessia , Martin-Gallausiaux Camille , Halder Rashi , Huarte Oihane Uriarte , Heurtaux Tony , Heins-Marroquin Ursula , Gomez-Giro Gemma , Weidenbach Katrin , Delacour Léa , Laczny Cédric , Novikova Polina , Ramiro-Garcia Javier , Singh Randolph , Andújar Begoña Talavera , Lebrun Laura , Daujeumont Annegrait , Habier Janine , Dong Xiangyi , Gavotto Floriane , Heintz-Buschart Anna , Schneider Jochen , Jehmlich Nico , von Bergen Martin , Schymanski Emma , Schmitz Ruth , Schwamborn Jens , Glaab Enrico , Linster Carole , Kitami Toshimori , Buttini Manuel , May Patrick , Trenkwalder Claudia , Oertel Wolfgang , Mollenhauer Brit 
Published: July 2022

Abstract
Patients with Parkinson’s disease (PD) exhibit differences in their gut microbiomes compared to healthy individuals. Although differences have most commonly been described in the abundances of bacterial taxa, changes to viral and archaeal populations have also been observed. Mechanistic links between gut microbes and PD pathogenesis remain elusive but could involve molecules that promote α-synuclein aggregation. Here, we show that 2-hydroxypyridine (2-HP) represents a key molecule for the pathogenesis of PD. We observe significantly elevated 2-HP levels in faecal samples from patients with PD or its prodrome, idiopathic REM sleep behaviour disorder (iRBD), compared to healthy controls. 2-HP is correlated with the archaeal species Methanobrevibacter smithii and with genes involved in methane metabolism, and it is detectable in isolate cultures of M. smithii. We demonstrate that 2-HP is selectively toxic to transgenic α-synuclein overexpressing yeast and increases α-synuclein aggregation in a yeast model as well as in human induced pluripotent stem cell derived enteric neurons. It also exacerbates PD-related motor symptoms, α-synuclein aggregation, and striatal degeneration when injected intrastriatally in transgenic mice overexpressing human α-synuclein. Our results highlight the effect of an archaeal molecule in relation to the gut-brain axis, which is critical for the diagnosis, prognosis, and treatment of PD.
Characterization of a multifunctional biocontrol agent, Streptomyces Misakimycin, against Newcastle Disease Virus
Authors: Abdelaziz Rewan , Barakat Ahmed B. , EL-Didamony Gamal , Tartor Yasmine H. , Gado Marwa M. , El-Samadony Hanaa A. 
Published: July 2022

Abstract
Background
The Newcastle Disease Virus (NDV) is present throughout the world, and outbreaks in Egypt caused serious economic losses in the poultry industry. Actinobacteria are a phylum of bacteria known for their potential in producing structurally diversified natural products which promising natural compounds used to combat viruses are presented and evaluated. Streptomyces Misakimycin isolated from Egyptian soil, and evaluated for their efficacy in controlling NDV. On the basis of the biochemical characteristics S. Misakimycin metabolites, identified by infrared (IR) and nuclear magnetic resonance (NMR) spectroscopy.
Results
In this investigation, NDV was found to have been isolated in February from a chicken farm in the Dakahlia Governorate of Egypt by the Animal Health Research Institute in Dokki, Giza. Diethylpthalate (DEP), a secondary metabolite of S. misakimycin, completely inhibited the hemagglutination (HI) activity of the NDV strain (MN635617) at log107 infectivity titers (EID50/mL). With 0.5 percent and 0.75 percent of chicken RBCs, the HA of the NDV strain was 2 log2 and 5 log2, respectively. In the treated group that received DEP and NDV inoculations, chorioallantoic-membranes (CAM) structures were preserved along with dilated capillary networks. Histological changes in SPF-ECE liver were examined after inoculation in ova to further characterize the DEP effect. Diethylpthalate and NDV mixture inoculated group showed preserved cytoarchitecture of hepatocytes with the presence of perivascular foci of lymphocytes. The group that was inoculated with telomycin alone showed normal histology of hepatic acini, central veins, and portal triads.
Conclusion
A potentially bioactive substance called diethylpthalate has the potential to be a biological weapon against a fatal chicken NDV that quickly increase cost losses for farmers.
The Impact of Atrophic Gastritis and Intestinal Metaplasia on the Occurrence of Metachronous Gastric Cancer After Endoscopic Resection: A Systematic Review and Meta-analysis
Authors: Choe Younghee , Park Jae Myung , Kim Joon Sung , Cho Yu Kyung , Kim Byung-Wook , Choi Myung-Gyu 
Published: July 2022

Abstract
Background: Metachronous gastric cancer (MGC) can occur after endoscopic resection for gastric cancer. This systematic review and meta-analysis aimed to evaluate the risk of MGC caused by severe atrophic gastritis (AG) and intestinal metaplasia (IM).Methods: We searched the medical literature through May 2022 and identified patients who occurred MGC after endoscopic resection for gastric cancer. We retrieved studies evaluating the degree of AG and the presence or absence of IM and compared the incidence of MGC, respectively.Results: From nine cohort studies, 2,755 patients by 2018. Incidence of MGC was significantly higher in severe AG (RR, 1.64; 95% CI, 1.29–2.07; I2=45%) and IM (RR, 7.08; 95% CI, 3.63–13.80; I2=0%) than those without. The absolute risk difference of MGC in severe AG and IM was 7.5% and 9.2%, respectively. The difference in incidence rate per 1000 person-years was 17.5 and 22.5 person-years, respectively. However, the H. pylori infection did not affect the MGC occurrence (RR 1.08, 95% CI 0.85–1.39, I2=0%).Conclusions: Severe AG or IM had a 1.6-fold and 7.0-fold higher risk of MGC occurrence after endoscopic resection of gastric cancer. Patients with severe AG or IM need more stringent follow-up to monitor MGC occurrences.
The H3 K27-altered, Extent of Resection and Survival in Pediatric High-grade Spinal Cord Gliomas
Authors: Yu Qi-Shuai , Zhang Fan , Fan Tao , Yu Xin-Guang 
Published: July 2022

Abstract
Purpose
Pediatric high-grade spinal cord gliomas (pHGSG) are classified into two prognostically meaningful subtypes. The purpose of our study is to describe clinical characteristics and management of two pHGSG subtypes, especially focus on the effect of surgical resection in these two subtypes.
Methods
We described the clinical characteristics and management and analyzed the prognostic factors of 19 pHGSGs. Based on H3 K27-altered and isocitrate dehydrogenase (IDH) mutation status, pHGSGs were classified into H3 K27-altered and H3/IDH-wildtype pHGSG for assessing effect of surgical resection.
Results
Nineteen patients (11 males and 8 females) with a mean age of 12.7 ± 4.7 years were included in the analysis. The median survival time of all patients was 14 months. Thirteen pHGSG patients had H3 K27-altered tumors, and 6 had H3/IDH-wildtype tumors. All patients received therapeutic surgical resection, 10 (55.6%) patients underwent gross total resection (GTR) and 8 (33.3%) patients underwent subtotal resection (STR). pHGSG patients with H3 K27-altered underwent GTR (HR 0.311, 95% CI 0.075–1.289, p = 0.091) had tended to increase overall survival. For patients of H3/IDH-wildtype pHGSG, there was no survival advantage associated with GTR (p = 0.157).
Conclusions
The extent of surgical resection has the different effects on survival in H3 K27-altered and H3/IDH-wildtype pHGSGs. The patients with H3 K27-altered pHGSG have tended to benefit from a greater extent of surgical resection. Nevertheless the benefit was not evident in the patients with H3/IDH-wildtype pHGSG.
A novel method for image captioning using multimodal feature fusion employing mask recurrent neural networks and long short term memory
Authors: Thangavel Kumaravel , Palanisamy Natesan , Muthusamy Suresh , Panchal Hitesh 
Published: July 2022

Abstract
The image captioning is a technique that allows us to use computers to interpret the information of photographs and make written text. The use of deep learning to interpret image information and create descriptive text has become a widely researched issue since its establishment. Nevertheless, these strategies do not identify all samples that depict conceptual ideas. By reality, the vast majority of them seem to be irrelevant to the matching tasks. The degree of similarity is determined only by a few relevant semantics occurrences. These duplicate instances can also be thought of as noise, as they obstruct the matching process of a few meaningful instances and add to the model's computational effort. Furthermore, present approaches frequently require deliberate use of additional target recognition algorithms or costly human labelling in the extracting information is required.For image captioning, this research presents a multi-modal feature fusion based deep learning model. The coding layer uses Mask Recurrent Neural Networks (Faster R-CNN), the long short-term memory (LSTM)-attend has been used to decoding, and the descriptive text is constructed.In deep learning, the model parameters are optimized through method gradients optimization. In the decoding layer, dense attention mechanisms can assist in minimizing non-salient data interruption and preferentially input the appropriate comprised for the decryption stage. The model's capacity to comprehend images and generate text is validated by the experimental data in the domain of generic images. This paper is implemented using Python frameworks and also evaluated using the performance metrics such as PSNR, RMSE, SSIM, Accuracy, Recall, F1-score and Precision.
The Interaction of Specific Frequency Bands in the Geomagnetic Field Diurnal Spectrum, With Specific Frequency Bands in the Human Heart Rate Variability Diurnal Spectrum.
Authors: Davies Elizabeth Anne 
Published: July 2022

Abstract
BACKGROUND.
For over 50 years, experiments have been demonstrating an interaction between the dynamics of the human heart and the dynamics of the earth’s magnetic field. In these experiments, specific frequency components in the variability of the geomagnetic field (GMF), involving micropulsations, are shown to significantly interact with specific frequency components in human heart rate variability (HRV). A significant difference was found in the HRV ratio of VLF/HF, on days of low geomagnetic variability (L gmf) compared with days of high geomagnetic field variability (H gmf) (P = 0.0001, n = 24, effect size 1.014).
METHODS.
Experiments were conducted prospectively, over a period of 3 years, on one 70 year old, healthy female subject, using a 24 hour holter electrocardiogram (ECG) machine, and the results were analysed for the HRV frequency spectral components. The local geomagnetic field was simultaneously monitored over 24 hour periods, using a 3-axis fluxgate magnetometer, and the frequency spectra were analysed for the various spectral power components. Statistical analysis was performed using XLSTAT software.
RESULTS.
It was shown that there was a correspondence in the power spectra of the high (HF) and very low (VLF) frequency components in HRV and GMF variability. It was shown that there was a significant difference in the ratio of the VLF and HF frequency band power of the HRV between the ECGs recorded during days of lower geomagnetic variability, and days of higher geomagnetic variability.
CONCLUSION.
These findings support the hypothesis of a homeostatic response of the human heart to the earth’s magnetic field. This may have implications for prognosis and management of heart disease, during times of significant environmental change.
Safety and efficacy of host-associated Latilactobacillus curvatus strains for potential probiotic applications in farmed Atlantic salmon (Salmo salar)
Authors: Cathers Hannah S. , Mane Shrinivasrao P. , Tawari Nilesh R. , Balakuntla Jayanth , Plata Germán , Krishnamurthy Madan , MacDonald Alicia , Wolter Marilyn , Baxter Niel , Briones Julian , Nagireddy Akshitha , Millman Gregory , Martin Roberto E. , Kumar Arvind , Gangaiah Dharanesh 
Published: July 2022

Abstract
Salmon aquaculture is the fastest growing animal protein production system in the world; however, intensive farming leads to poor weight gain, stress, and disease outbreaks. Probiotics offer the potential to enhance growth performance and feed efficiency in Atlantic salmon, as well as immunostimulate fish against common pathogens, benefitting farmers and consumers with more efficient production. Here, we isolated and identified 900 native microbial isolates including 18 Lactobacilli from farmed salmon intestines. Based on whole-genome sequencing and phylogenetic analysis, the Lactobacillus candidates belonged to Latilactobacillus curvatus (L. curvatus) species and formed two distinct phylogenetic groups. Using bioinformatics and in vitro analyses, we selected two candidates L. curvatus ATCC PTA-127116 and L. curvatus ATCC PTA-127117, which showed desirable safety and probiotic properties. The two L. curvatus candidates were evaluated for safety and efficacy in Atlantic salmon alongside spore-forming Bacilli isolated from salmon, poultry, and swine. All the tested candidates were safe to salmon with no adverse effects. While we did not see efficacy in any Bacillus supplemented groups, compared to untreated group, the group administered with the two L. curvatus strains consortium in feed for seven weeks showed significant improvement in final body weight by 4.2%. Similarly, the two L. curvatus candidates were also evaluated for safety and efficacy in Atlantic salmon in saltwater; the group administered with the two L. curvatus strains consortium in feed for 11 weeks showed significant improvement in final body weight by 4.7%. Comprehensive metabolomics analyses in the presence of different prebiotics and/or additives identified galactooligosaccharide as a potential prebiotic to enhance the efficacy of two L. curvatus candidates. All together, these data provide in silico and in vivo evidence of safety and efficacy of two novel endogenous L. curvatus candidates for potential economical and sustainable probiotic applications in salmon and likely other aquatic species.
Distribution of relief items with specific demand and inventory constraints using a multi-product optimization model
Authors: Singh Jitendra , Jaggi Chandra K. 
Published: July 2022

Abstract
The humanitarian relief chain is one of the most critical components of a disaster relief operation. The present work develops a nonlinear programming approach for disaster relief logistics under risk with uncertainty. In this approach, demands and supplies and the cost of inventory and transportation are considered depending on the severity of the disaster. Furthermore, the model considers the demand for the affected locations where the demand fluctuates due to the new entrants and individuals leaving relief camps. The discussed multi-product inventory relief chain model attempts to minimize the sum of the relief chain's transportation and total costs while considering inventory and disposal of damaged units. The transportation cost is affected by the severity of the disaster and a risk factor associated with affected locations. Assuming these costs, mixed-integer nonlinear programming is constructed and demonstrated with a numerical example. A numerical example with sensitivity analysis with multiple cost parameters is presented to improve relief supply chain planning in disaster scenarios. The results suggest that the proposed model can help decision-making about facility location and relief supplies distribution during disaster relief efforts.
The behaviour of the Gauss-Radau upper bound of the error norm in CG
Authors: Meurant Gérard , Tichý Petr 
Published: July 2022

Abstract
Consider the problem of solving systems of linear algebraic equations Ax=b with a real symmetric positive definite matrix A using the conjugate gradient (CG) method. To stop the algorithm at the appropriate moment, it is important to monitor the quality of the approximate solution. One of the most relevant quantities for measuring the quality of the approximate solution is the A-norm of the error. This quantity cannot be easily evaluated, however, it can be estimated. In this paper we discuss and analyze the behaviour of the Gauss-Radau upper bound on the A-norm of the error, based on viewing CG as a procedure for approximating a certain Riemann-Stieltjes integral. This upper bound depends on a prescribed underestimate μ to the smallest eigenvalue of A. We concentrate on explaining a phenomenon observed during computations showing that, in later CG iterations, the upper bound loses its accuracy, and it is almost independent of μ. We construct a model problem that is used to demonstrate and study the behaviour of the upper bound in dependence of μ, and developed formulas that are helpful in understanding this behavior. We show that the above mentioned phenomenon is closely related to the convergence of the smallest Ritz value to the smallest eigenvalue of A. It occurs when the smallest Ritz value is a better approximation to the smallest eigenvalue than the prescribed underestimate μ. We also suggest an adaptive strategy for improving the accuracy of the Gauss-Radau upper bound such that the resulting estimate approximates the quantity of interest with a prescribed relative accuracy.