bluuebunny/crossref_metadata_2025_split huggingface dataset:
Untangling Magellanic Streams
Authors: Zaritsky Dennis , Chandra Vedant , Conroy Charlie , Bonaca Ana , Cargile Phillip A. , Naidu Rohan P. 
Published: November 2024

The Magellanic Stream has long been known to contain multiple HI strands and corresponding stellar populations are beginning to be discovered. Combining an H3-selected sample with stars drawn from the Gaia catalog, we trace stars along a sub-dominant strand of the Magellanic Stream, as defined by gas content, across 30∘ on the sky. We find that the dominant strand is devoid of stars with Galactocentric distance \(\lesssim 55\) kpc while the subdominant strand shows a close correspondence to such stars. We conclude that (1) the two Stream strands have different origins, (2) they are likely only close in projection, (3) the subdominant strand is tidal in origin, and (4) the subdominant strand is composed of disk material, likely drawn from the disk of the Small Magellanic Cloud. _Subject headings:_ Magellanic Clouds (990), Magellanic Stream (991), Milky Way stellar halo (1060)
Outer Solar System Spacecraft Without Drag-Free Control to Probe the μHz Gravitational Wave Frontier
Authors: McQuinn Matthew , McGrath Casey 
Published: November 2024

The microhertz frequency band of gravitational waves probes the merger of supermassive black holes as well as many other gravitational wave phenomena. However, space-interferometry methods that use test masses would require substantial development of test-mass isolation systems to detect anticipated astrophysical events. We propose an approach that avoids inertial test masses by situating spacecraft in the low-acceleration environment of the outer Solar System. We show that for Earth-spacecraft and inter-spacecraft distances of \(\gtrsim 10\)AU, the accelerations on the spacecraft would be sufficiently small to potentially achieve sensitivities determined by stochastic gravitational wave backgrounds. We further argue, for arm lengths of \(10 - 30\)AU and \(10\)Watt transmissions, that stable phase locks should be achievable with 20 cm mirrors or \(5\) m radio dishes. We discuss designs that send both laser beams and radio waves between the spacecraft, finding that despite the \(\sim 10^{4} \times\) longer wavelengths, even a design with radio transmissions could reach stochastic background-limited sensitivities at \(\lesssim {0.3 \times 10^{- 4}}\)Hz. Operating in the radio significantly reduces many spacecraft design tolerances. Our baseline concept requires two arms to do interferometry. However, if one spacecraft carries a clock with Allan deviations at \(10^{4}\) seconds of \(10^{- 17}\), a comparable sensitivity could be achieved with a single arm. Finally, we discuss the feasibility of achieving similar gravitational wave sensitivities in a ‘Doppler tracking’ configuration where the single arm is anchored to Earth.
Comparing BDD and TDD: Machine Learning Analysis of Software Quality with SHAP Interpretability
Authors: Airlangga Gregorius 
Published: November 2024

This study evaluates the impact of Behavior-Driven Development (BDD) and Test-Driven Development (TDD) on software quality using machine learning models, including Random Forest, XGBoost, and LightGBM. Key metrics such as bug detection, test coverage, and development time were analyzed using a dataset from multiple software projects. Polynomial feature expansion captured non-linear interactions, while SHapley Additive exPlanations (SHAP) enhanced interpretability. Results indicate that Random Forest achieved the best predictive accuracy, with an average RMSE of 7.64 and MAE of 6.39, outperforming XGBoost (average RMSE: 8.63, MAE: 7.37) and LightGBM (average RMSE: 6.89, MAE: 5.38). However, negative values across all models reveal challenges in generalization. SHAP analysis highlights the critical influence of higher-order interactions, particularly between test coverage and development time. These findings underscore the complexity of predicting software quality and suggest the need for additional features and advanced techniques to enhance model performance. This study provides a comprehensive, interpretable framework for assessing the comparative effectiveness of BDD and TDD in improving software quality.
Phytochemical profiling and in silico evaluation of Artemisia absinthium compounds targeting Leishmania N-myristoyltransferase: molecular docking, drug-likeness, and toxicity analyses
Authors: Boudou Farouk , Belakredar Amal , Berkane Alaeddine , Keziz Ahcen , Alsaeedi Huda , Cornu David , Bechelany Mikhael , Barhoum Ahmed 
Published: November 2024

BackgroundArtemisia absinthium has long been recognized for its therapeutic properties against various diseases. Among these is leishmaniasis, a parasitic infection that remains a global health challenge. Targeting Leishmania N-myristoyltransferase (NMT), a crucial enzyme for parasite survival, represents a promising therapeutic approach. The bioactive compounds in A. absinthium could potentially inhibit NMT and serve as new treatment options for leishmaniasis.AimThis study aims to investigate the phytochemical composition, drug-likeness, and molecular dynamics of A. absinthium bioactive compounds targeting Leishmania NMT, identifying potent inhibitors that could serve as new drug candidates.MethodThe extract of A. absinthium was analyzed using High-Performance Liquid Chromatography (HPLC), identifying nine phenolic compounds, with kaempferol (10.72%) and chlorogenic acid (4.43%) being the most abundant. Drug-likeness and toxicity were evaluated using SwissADME and OSIRIS Property Explorer, focusing on adherence to Lipinski’s rule of five and Ghose’s filter. Molecular docking studies were conducted to evaluate the binding affinity of these compounds to NMT. Molecular dynamics (MD) simulations were performed to assess the stability and flexibility of the NMT-apigenin complex.ResultsMolecular docking identified apigenin as the most potent NMT inhibitor, with a binding energy of −9.6 kcal/mol, forming significant hydrogen bonds with threonine residues 203 and 189. Drug-likeness analysis revealed that most compounds adhered to Lipinski’s rule of five, indicating favorable pharmacokinetic properties. MD simulations confirmed the stability of the NMT-apigenin complex, with root mean square deviation (RMSD) values of 0.04 nm, root mean square fluctuation (RMSF) values between 0.05 and 0.35 nm, and radius of gyration (Rg) values ranging from 2.24 to 2.30 nm. Normal mode analysis further supported the complex’s stability and flexibility.ConclusionThe findings of this study underscore the potential of Artemisia absinthium compounds, particularly apigenin, as promising candidates for the development of new anti-leishmaniasis drugs. The potent inhibition of Leishmania NMT by apigenin, along with its favorable pharmacokinetic and stability profiles, supports its further exploration in antileishmanial drug development.
Structure-based targeting of the lipid A-modifying enzyme PmrC to contrast colistin resistance in Acinetobacter baumannii
Authors: Romano Maria , Falchi Federico , De Gregorio Eliana , Stabile Maria , Migliaccio Antonella , Ruggiero Alessia , Napolitano Valeria , Autiero Ida , Squeglia Flavia , Berisio Rita 
Published: November 2024

IntroductionAntimicrobial-resistant pathogens are an ongoing threat to human and animal health. According to the World Health Organization (WHO), colistin is considered the last resort antibiotic against human infections due to multidrug-resistant Gram-negative organisms—including Acinetobacter baumanni, a priority-1 pathogen. Despite colistin being considered a last resort antibiotic, transferable bacterial resistance to this drug has been reported in humans and animals. This makes addressing colistin resistance a critical priority in public health efforts. The large PetN transferase membrane protein PmrC is responsible for colistin resistance due to its catalysed modification of lipid A of the external membrane. Despite its importance, this potential drug target was never characterised at a molecular level.MethodsThe recombinant production of large membrane proteins in their native forms is a bottleneck in modern molecular biology. In this study, we recombinantly produced PmrC and biophysically characterised it in solution. We employed in silico approaches, including virtual screening and molecular modelling, to identify PmrC ligands. The binding of these ligands to PmrC was measured using Microscale Thermophoresis (MST). The best ligand was tested for its ability to hamper colistin resistance in Acinetobacter baumannii clinical isolates. Finally, we checked that the identified compound was not cytotoxic at the used concentrations by haemolysis assays.ResultsWe successfully produced PmrC PetN transferase membrane protein in high yields and showed that PmrC is a stable α-β protein, with melting temperature Tm = 60°C. Based on the PmrC structural model, we identified a promising druggable cavity. Therefore, we used a structure-based virtual screening to identify potential inhibitors. A small molecule, here denominated as s-Phen, was proved to bind PmrC with μM affinity. Microbiological assays confirmed that the s-Phen can drastically reduce colistin minimum inhibitory concentration (MIC) in two A. baumannii-resistant isolates and that it is not cytotoxic. Importantly, PmrC binding pocket to s-Phen is highly conserved in all homologues of PmrC, regardless of the location of genes encoding for them and of their operons.DiscussionOur study provides a molecular characterisation of PmrC and demonstrates the importance of PmrC as a drug target and the strong potential of PmrC binding molecules to act as colistin adjuvants, operating as synergistic tools to combat multiresistant nosocomial pathogens.
The ameliorative effect of chrysin on ovarian toxicity caused by methidathion in female rats
Authors: Hamed Amany M. , Ali Fatma Abo Zakaib , Mohammed Ard elshifa M. E. , Alrasheedi Muneera , Ragab Islam , Aldoghaim Maryam , Soliman Safaa S. 
Published: November 2024

Introduction: Methidathion (MD) is commonly used in agriculture and has adverse effects on reproduction. Chrysin (CHR) has several advantageous properties, such as anti-inflammatory, anti-cancer, and antioxidant properties. The purpose of the current investigation was to assess CHR’s therapeutic efficacy in reducing ovarian toxicity brought on by MD.Methods: Twenty-four female rats were divided into four groups of six animals each. Group 1 served as a control, while group 2 rats received MD (5 mg/kg). Rats in Group 3 received CHR at a dose of 50 mg/kg. Rats in group 4 received treatment with CHR after MD intoxication.Results and Discussion: Our research revealed that MD significantly (p &lt; 0.001) increased the levels of MDA, caspase-3, FSH, LH, CA-125, and TNF-α but significantly (p &lt; 0.001) decreased the levels of SOD, GSH, E2, and progesterone when compared to the control and CHR groups. After receiving CHR therapy, damage induced by MD was significantly (p &lt; 0.001) repaired.Conclusion: This study showed that CHR could mitigate the adverse effects that MD causes to the ovaries by decreasing oxidative stress, inflammation, and apoptosis; improving antioxidant status; and restoring the correct ratio of sex hormones.
Trade-offs among brain structural network characteristics across the cognitive decline process in cerebral small vessel disease
Authors: Wang Yao , Liu Mianxin , Chen Yuewei , Qiu Yage , Han Xu , Xu Qun , Shen Dinggang , Zhou Yan 
Published: November 2024

ObjectivesTo investigate the potential trade-offs among brain structural network characteristics across different stages of cognitive impairment in cerebral small vessel disease (CSVD) based on diffusion tensor imaging (DTI).MethodsA total of 264 CSVD patients, including 95 patients with non-cognitive impairment (NCI), 142 with mild cognitive impairment (MCI), 27 with vascular dementia (VaD), and 30 healthy controls (HC) underwent cognitive test and brain diffusion magnetic resonance imaging (MRI). The brain structural network was constructed using connections between 90 cortical and subcortical regions. Network characteristics, including sparsity, redundancy, global efficiency (Eg), and local efficiency (Eloc), were calculated.ResultsSparsity and redundancy significantly declined in the NCI group compared to the HC group. Eg was significantly reduced in the MCI group compared to the NCI group. All network characteristics declined in the VaD group compared to the MCI group. In the NCI group, both sparsity and redundancy were significantly positively correlated with Montreal Cognitive Assessment (MoCA). In the MCI group, there was significant positive correlation between Eg and MoCA. In the VaD group, there was significant negative correlation between Eloc and MoCA. When controlling for sparsity, Eloc exhibited a significant negative correlation with Eg in all three CSVD groups, while redundancy displayed a significant negative correlation with Eg specifically in MCI group.ConclusionOur study provides evidence for the heterogeneous alterations in brain structural network across different stages of cognitive impairment in CSVD. The disconnection of brain structural network at NCI stage is mainly the loss of redundant connections. The decline of Eg is the vital factor for cognitive impairment at MCI stage. The decline of all network characteristics is the prominent manifestation at VaD stage. Throughout the cognitive decline process in CSVD, there are trade-offs among the brain network wiring cost, integration, and segregation.
Predicting grade II-IV bone marrow suppression in patients with cervical cancer based on radiomics and dosiomics
Authors: Tang Yanchun , Pang Yaru , Tang Jingyi , Sun Xinchen , Wang Peipei , Li Jinkai 
Published: November 2024

ObjectiveThe objective of this study is to develop a machine learning model integrating clinical characteristics with radiomics and dosiomics data, aiming to assess their predictive utility in anticipating grade 2 or higher BMS occurrences in cervical cancer patients undergoing radiotherapy.MethodsA retrospective analysis was conducted on the clinical data, planning CT images, and radiotherapy planning documents of 106 cervical cancer patients who underwent radiotherapy at our hospital. The patients were randomly divided into training set and test set in an 8:2 ratio. The radiomic features and dosiomic features were extracted from the pelvic bone marrow (PBM) of planning CT images and radiotherapy planning documents, and the least absolute shrinkage and selection operator (LASSO) algorithm was employed to identify the best predictive characteristics. Subsequently, the dosiomic score (D-score) and the radiomic score (R-score) was calculated. Clinical predictors were identified through both univariate and multivariate logistic regression analysis. Predictive models were constructed by intergrating clinical predictors with DVH parameters, combining DVH parameters and R-score with clinical predictors, and amalgamating clinical predictors with both D-score and R-score. The predictive model’s efficacy was assessed by plotting the receiver operating characteristic (ROC) curve and evaluating its performance through the area under the ROC curve (AUC), the calibration curve, and decision curve analysis (DCA).ResultsSeven radiomic features and eight dosiomic features exhibited a strong correlation with the occurrence of BMS. Through univariate and multivariate logistic regression analyses, age, planning target volume (PTV) size and chemotherapy were identified as clinical predictors. The AUC values for the training and test sets were 0.751 and 0.743, respectively, surpassing those of clinical DVH R-score model (AUC=0.707 and 0.679) and clinical DVH model (AUC=0.650 and 0.638). Furthermore, the analysis of both the calibration and the DCA suggested that the combined model provided superior calibration and demonstrated a higher net clinical benefit.ConclusionThe combined model is of high diagnostic value in predicting the occurrence of BMS in patients with cervical cancer during radiotherapy.
Nonlinear dynamic characteristics of wind power concentric planetary-face gear system with elastic lubrication and friction considering thermal effect under random wind load
Authors: Xincheng Bi , Jungang Wang , Ruina Mo 
Published: November 2024

IntroductionPlanetary-face gears combine the advantages of both planetary and face gears, offering potential value for wind power applications. During the gear meshing process, a large amount of heat is generated, and tooth wear also occurs, which affects transmission performance.MethodsAnalyzing multiple factors such as lubrication performance and thermal effects of meshing pairs plays a crucial role in improving the overall lifespan of transmission systems. This study developed a nonlinear dynamic model of a wind power planetary-face gear system, considering factors like random wind load, tooth surface friction, temperature rise, tooth side clearance, and elastic lubrication. Nonlinear methods such as bifurcation diagram, maximum Lyapunov exponent diagram, and time-frequency diagram were used to analyze the effects of wind turbine radius, average wind load, temperature rise, and lubricant viscosity on the dynamic response of the gear transmission system under random wind loads.ResultsThe results show that selecting an appropriate wind turbine radius for different wind loads is essential to enhance system stability. Higher lubricant viscosity can suppress chaotic phenomena in gear systems. For a well lubricated gear system, tooth surface temperature rise is a key factor affecting the dynamic characteristics of the system.DiscussionThis article aims to provide valuable insights into improving the operational stability of the wind turbine planetary gear system.
MaxEnt and Marxan modeling to predict the potential habitat and priority planting areas of Coffea arabica in Yunnan, China under climate change scenario
Authors: Li Xia , Wang Zihao , Wang Shaoqiang , Qian Zhaohui 
Published: November 2024

IntroductionCoffea arabica (Arabica coffee) is an important cash crop in Yunnan, China. Ongoing climate change has made coffee production more difficult to sustain, posing challenges for the region’s coffee industry. Predictions of the distribution of potentially suitable habitats for Arabica coffee in Yunnan could provide a theoretical basis for the cultivation and rational management of this species.MethodsIn this study, the MaxEnt model was used to predict the potential distribution of suitable habitat for Arabica coffee in Yunnan under current and future (2021-2100) climate scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) using 56 distributional records and 17 environmental variables and to analyze the important environmental factors. Marxan model was used to plan the priority planting areas for this species at last.ResultsThe predicted suitable and sub-suitable areas were about 4.21×104 km2 and 13.87×104 km2, respectively, accounting for 47.15% of the total area of the province. The suitable areas were mainly concentrated in western and southern Yunnan. The minimum temperature of the coldest month, altitude, mean temperature of the wettest quarter, slope, and aluminum saturation were the main environmental variables affecting the distribution of Arabica coffee in Yunnan Province. Changes in habitat suitability for Arabica coffee were most significant and contracted under the SSP3-7.0 climate scenario, while expansion was highest under the SSP5-8.5 climate scenario. Priority areas for Arabica coffee cultivation in Yunnan Province under the 30% and 50% targets were Pu’er, Xishuangbanna, Honghe, Dehong, and Kunming.DiscussionClimate, soil, and topography combine to influence the potential geographic distribution of Arabica coffee. Future changes in suitable habitat areas under different climate scenarios should lead to the delineation of coffee-growing areas based on appropriate environmental conditions and active policy measures to address climate change.
Parental democratic communication and adolescent well-being in an era of loneliness: the mediating role of societal trust
Authors: Liu Simin , Hu Sydney X. , Su Lanxin 
Published: November 2024

BackgroundIn an era marked by increasing loneliness, understanding the impact of parenting practices on adolescent well-being and resilience is crucial. This study investigates the relationship between parental democratic communication and key indicators of adolescent adjustment and well-being in China, with a focus on the mediating role of societal trust.ObjectiveThe study aimed to examine the direct effects of parental democratic communication on Chinese adolescents’ subjective well-being and to explore the mediating roles of societal trust in this relationship.MethodsData were collected from 691 high school students as part of the 2020 Chinese Family Panel Studies (CFPS). The sample was divided into two age groups: 16-17 years old (n=493) and 18 years old (n=198). Multi-group Structural Equation Modeling (SEM) was used to analyze the data.ResultsSEM analysis revealed age-specific effects of parental democratic communication (PDC) on subjective well-being (SWB). For ages 16-17, PDC directly influenced SWB (β=0.269, p&lt;0.001) with significant serial mediations through societal trust, negative emotion, and pleasant life experiences. For 18-year-olds, only societal trust mediated the PDC-SWB relationship (β=0.16, p&lt;0.01). Meanwhile, the effect of societal trust is superior to that of other mediating variables in both groups. Multi-group analysis showed measurement invariance but differences in structural relationships across age groups.ConclusionsParental democratic communication has a direct as well as serial mediated impact on mid-adolescents’ subjective well-being and an indirect impact through societal trust in late adolescence, among Chinese adolescents. These results point to a pattern we term “Societal Trust-Mediated Well-Being,” which appears to wield greater influence than negative emotions or pleasant life experiences, particularly among older adolescents. These results underscore the need for developmentally tailored approaches and integrative interventions that adapt to the changing dynamics of adolescent well-being in a rapidly evolving society.
EFFECT OF ANTIOXIDANTS TO CONTROL BROWNING IN GUAVA SOFT WOOD CUTTINGS
Authors: Abbas Mohsin , Aslam Komal , Mahreen Nida , Aziz Maaz , Sharif Naseem , Anjum Qamar Shehzad , Zahid Muhammad Talha Bin 
Published: November 2024

Guava is the Apple of tropics and becoming the popular fruit of Pakistan. Guava is a nutraceutical fruit enriched with important minerals and vitamins like ascorbic acid. To overcome upon the issue of brown spots on fruit rind of guava soft wood cuttings, a research trial is executed. /the experiment was planned to overcome the problem of brown spots on fruit rind in soft wood cuttings of guava. For this purpose antioxidants i.e Vitamin C and L-ascorbate were used as blend mixture with IBA (rooting hormone) used for the initiation of roots in cuttings. A research trial was performed by employing randomized complete block design having three replications including frour treatments. Data subjected to result interpretation revealed that there is success (92.28%) and survival percentage (42.06%) was found maximum in T3 wherease, IBA 0.4% was used in combination with 1.5% citric acid and 1.5% ascorbic acid. In case of vegetative parameters maximum plant height (24.06 cm), number of leaves (25.50), leaf area (51.43mm), number of branches (3.68) and branch length (12.69 cm) were observed in T3 as compared to other treatments. The highest values for root parameters like primary roots (21.17), secondary roots (45.94), root volume (2.26 cm3) and root length (9.65 cm) were found in treatment 3 while lowest values for all treatments were observed in control.