bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enantioselective synthesis of chiral α,α-dialkyl indoles and related azoles by cobalt-catalyzed hydroalkylation and regioselectivity switch
Authors: Ren Jiangtao , Sun Zheng , Zhao Shuang , Huang Jinyuan , Wang Yukun , Zhang Cheng , Huang Jinhai , Zhang Chenhao , Zhang Ruipu , Zhang Zhihan , Ji Xu , Shao Zhihui 
Published: May 2024

AbstractGeneral, catalytic and enantioselective construction of chiral α,α-dialkyl indoles represents an important yet challenging objective to be developed. Herein we describe a cobalt catalyzed enantioselective anti-Markovnikov alkene hydroalkylation via the remote stereocontrol for the synthesis of α,α-dialkyl indoles and other N-heterocycles. This asymmetric C(sp3)−C(sp3) coupling features high flexibility in introducing a diverse set of alkyl groups at the α-position of chiral N-heterocycles. The utility of this methodology has been demonstrated by late-stage functionalization of drug molecules, asymmetric synthesis of bioactive molecules, natural products and functional materials, and identification of a class of molecules exhibiting anti-apoptosis activities in UVB-irradiated HaCaT cells. Ligands play a vital role in controlling the reaction regioselectivity. Changing the ligand from bi-dentate L6 to tridentate L12 enables CoH-catalyzed Markovnikov hydroalkylation. Mechanistic studies disclose that the anti-Markovnikov hydroalkylation involves a migratory insertion process while the Markovnikov hydroalkylation involves a MHAT process.
Active site remodeling in tumor-relevant IDH1 mutants drives distinct kinetic features and potential resistance mechanisms
Authors: Mealka Matthew , Sierra Nicole A. , Avellaneda Matteo Diego , Albekioni Elene , Khoury Rachel , Mai Timothy , Conley Brittany M. , Coleman Nalani J. , Sabo Kaitlyn A. , Komives Elizabeth A. , Bobkov Andrey A. , Cooksy Andrew L. , Silletti Steve , Schiffer Jamie M. , Huxford Tom , Sohl Christal D. 
Published: May 2024

AbstractMutations in human isocitrate dehydrogenase 1 (IDH1) drive tumor formation in a variety of cancers by replacing its conventional activity with a neomorphic activity that generates an oncometabolite. Little is understood of the mechanistic differences among tumor-driving IDH1 mutants. We previously reported that the R132Q mutant unusually preserves conventional activity while catalyzing robust oncometabolite production, allowing an opportunity to compare these reaction mechanisms within a single active site. Here, we employ static and dynamic structural methods and observe that, compared to R132H, the R132Q active site adopts a conformation primed for catalysis with optimized substrate binding and hydride transfer to drive improved conventional and neomorphic activity over R132H. This active site remodeling reveals a possible mechanism of resistance to selective mutant IDH1 therapeutic inhibitors. This work enhances our understanding of fundamental IDH1 mechanisms while pinpointing regions for improving inhibitor selectivity.
A chromosome-level haplotype-resolved genome assembly of oriental tobacco budworm (Helicoverpa assulta)
Authors: Xu Yalong , Wang Chen , Li Zefeng , Zheng Xueao , Kang Zhengzhong , Lu Peng , Zhang Jianfeng , Cao Peijian , Chen Qiansi , Liu Xiaoguang 
Published: May 2024

AbstractOriental tobacco budworm (Helicoverpa assulta) and cotton bollworm (Helicoverpa armigera) are two closely related species within the genus Helicoverpa. They have similar appearances and consistent damage patterns, often leading to confusion. However, the cotton bollworm is a typical polyphagous insect, while the oriental tobacco budworm belongs to the oligophagous insects. In this study, we used Nanopore, PacBio, and Illumina platforms to sequence the genome of H. assulta and used Hifiasm to create a haplotype-resolved draft genome. The Hi-C technique helped anchor 33 primary contigs to 32 chromosomes, including two sex chromosomes, Z and W. The final primary haploid genome assembly was approximately 415.19 Mb in length. BUSCO analysis revealed a high degree of completeness, with 99.0% gene coverage in this genome assembly. The repeat sequences constituted 38.39% of the genome assembly, and we annotated 17093 protein-coding genes. The high-quality genome assembly of the oriental tobacco budworm serves as a valuable genetic resource that enhances our comprehension of how they select hosts in a complex odour environment. It will also aid in developing an effective control policy.
A comprehensive laser image dataset for real-time measurement of wheelset geometric parameters
Authors: Song Yuezeng , Ji Zhenyan , Guo Xiaoxuan , Hsu Yihan , Feng Qibo , Yin Shen 
Published: May 2024

AbstractRailway transportation has experienced significant growth worldwide, offering numerous benefits to society. Most railway accidents are caused by wheelset faults so it’s significant to monitor wheelset conditions. Therefore, we need to collect wheelset images, repaint them, extract laser stripe centerlines, construct 3D contour, and measure their geometric parameters to judge the wheelset’s conditions. Deep learning can fulfill the tasks satisfyingly because it’s adaptable, robust, and generalize compared with traditional methods. To train the deep learning models effectively, we need rich and high-quality wheelset datasets. So far, there are no applicable public train wheelset datasets available, which greatly hinders the research on train wheelsets. Thus we construct a publicly available Wheelset Laser Image Dataset (WLI-Set). WLI-Set consists of four sub-datasets, Original, Inpainting, Segmentation, and Centerline. The dataset contains abundant annotated multiline laser stripe images that can facilitate the research on train wheelsets effectively.
Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures
Authors: Giri Nabin , Wang Liguo , Cheng Jianlin 
Published: May 2024

AbstractThe advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structures of biological macromolecules and their complexes significantly expedite biomedical research and drug discovery. However, automatically and accurately building atomic models from high-resolution cryo-EM density maps is still time-consuming and challenging when template-based models are unavailable. Artificial intelligence (AI) methods such as deep learning trained on limited amount of labeled cryo-EM density maps generate inaccurate atomic models. To address this issue, we created a dataset called Cryo2StructData consisting of 7,600 preprocessed cryo-EM density maps whose voxels are labelled according to their corresponding known atomic structures for training and testing AI methods to build atomic models from cryo-EM density maps. Cryo2StructData is larger than existing, publicly available datasets for training AI methods to build atomic protein structures from cryo-EM density maps. We trained and tested deep learning models on Cryo2StructData to validate its quality showing that it is ready for being used to train and test AI methods for building atomic models.
Ecological weed management and square planting influenced the weed management, and crop productivity in direct-seeded rice
Authors: Nagargade Mona , Singh Manoj Kumar , Tyagi Vishal , Govindasamy Prabhu , Choudhary Anil K. , Rajpoot Kuldeep , Kumar Adarsh , Singh Preeti , Sarangi Debalin 
Published: May 2024

AbstractHerbicide use may pose a risk of environmental pollution or evolution of resistant weeds. As a result, an experiment was carried out to assess the influence of different non-chemical weed management tactics (one hoeing (HH) at 12 DAS followed by (fb) one hand weeding at 30 DAS, one HH at 12 DAS fb Sesbania co-culture and its mulching, one HH at 12 DAS fb rice straw mulching @ 4t ha−1, one HH at 12 DAS fb rice straw mulching @ 6 t ha−1) on weed control, crop growth and yield, and economic returns in direct-seeded rice (DSR). Experiment was conducted during kharif season in a split-plot design and replicated thrice. Zero-till seed drill-sown crop (PN) had the lowest weed density at 25 days after sowing (DAS), while square planting geometry (PS) had the lowest weed density at 60 DAS. PS also resulted in a lower weed management index (WMI), agronomic management index (AMI), and integrated weed management index (IWMI), as well as higher growth attributes, grain yield (4.19 t ha–1), and net return (620.98 US$ ha–1). The cultivar Arize 6444 significantly reduced weed density and recorded higher growth attributes, yield, and economic return. In the case of weed management treatments, one HH at 12 DAS fbSesbania co-culture and its mulching had the lowest weed density, Shannon-weinner index and eveness at 25 DAS. However, one hoeing at 12 DAS fb one hand weeding at 30 DAS (HH + WH) achieved the highest grain yield (4.85 t ha–1) and net returns (851.03 US$ ha–1) as well as the lowest weed density at 60 DAS. PS × HH + WH treatment combination had the lowest weed persistent index (WPI), WMI, AMI, and IWMI, and the highest growth attributes, production efficiency, and economic return.
Utilizing experimental design and desirability function in optimizing RP-HPLC method for simultaneous determination of some skeletal muscle relaxants and analgesics
Authors: Mozayad Ayoub N. , Fouad Marwa A. , Elkady Ehab F. 
Published: May 2024

AbstractAn experimental design and response surface methodologies using Plackett–Burman and Box-Behnken designs were applied for selecting and optimizing the most appropriate parameters which significantly affect the separation and quantitative estimation of five skeletal muscle relaxants and four analgesic drugs (baclofen, methocarbamol, dantrolene sodium, orphenadrine citrate, cyclobenzaprine hydrochloride, ketoprofen, etoricoxib, ibuprofen, and mefenamic acid) with a relatively short duration of analysis in a single run. For the separation of the nine drugs, an INERTSIL ODS-V3-5 µm C18 column (250 × 4.6 mm I.D.) was used with the optimum mobile phase conditions (45.15 mM ammonium acetate buffer pH 5.56 adjusted with acetic acid, acetonitrile, and methanol in a ratio of 30.5:29.5:40, v/v/v with a flow rate of 1.5 mL/min) and UV-detection at 220 nm. The optimized method was successfully subjected to the validation steps as described in ICH guidelines for linearity, precision, accuracy, robustness, and sensitivity. The optimized and validated method was effectively applied to determine the content of the studied drugs in their pharmaceutical preparations and to expand its applicability to the counterfeit estimation of etoricoxib in different brands of tablet dosage forms.
A longitudinal analysis of soil salinity changes using remotely sensed imageries
Authors: Bandak Soraya , Movahedi-Naeini Seyed Alireza , Mehri Saeed , Lotfata Aynaz 
Published: May 2024

AbstractSoil salinization threatens agricultural productivity, leading to desertification and land degradation. Given the challenges of conducting labor-intensive and expensive field studies and laboratory analyses on a large scale, recent efforts have focused on leveraging remote sensing techniques to study soil salinity. This study assesses the importance of soil salinity indices’ derived from remotely sensed imagery. Indices derived from Landsat 8 (L8) and Sentinel 2 (S2) imagery are used in Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Decision Tree (DT), and Support Vector Machine (SVR) are associated with the electrical (EC) conductivity of 280 soil samples across 24,000 hectares in Northeast Iran. The results indicated that the DT is the best-performing method (RMSE = 12.25, MAE = 2.15, R2 = 0.85 using L8 data and RMSE = 10.9, MAE = 2.12, and R2 = 0.86 using S2 data). Also, the results showed that Multi-resolution Valley Bottom Flatness (MrVBF), moisture index, Topographic Wetness Index (TWI), and Topographic Position Indicator (TPI) are the most important salinity indices. Subsequently, a time series analysis indicated a reduction in salinity and sodium levels in regions with installed drainage networks, underscoring the effectiveness of the drainage system. These findings can assist decision-making about land use and conservation efforts, particularly in regions with high soil salinity.
Causal impact evaluation of occupational safety policies on firms’ default using machine learning uplift modelling
Authors: Barile Berardino , Forti Marco , Marrocco Alessia , Castaldo Angelo 
Published: May 2024

AbstractIt is often undermined that occupational safety policies do not only displace a direct effect on work well-being, but also an indirect effect on firms’ economic performances. In such context, econometric models dominated the scenes of causality until recently while Machine Learning models were seen with skepticism. With the rise of complex datasets, an ever-increasing need for automated algorithms capable to handle complex non-linear relationships between variables has brought to uncover the power of Machine Learning for causality. In this paper, we carry out an evaluation of a public aid-scheme implemented in Italy and oriented to support investment of small and medium enterprises (SMEs) in occupational safety and health (OSH) for assessing the impact on the survival of corporations. A comparison of thirteen models is performed and the Individual Treatment Effect (ITE) estimated and validated based on the AUUC and Qini score for which best values of 0.064 and 0.407, respectively, are obtained based on the Light Gradient Boosting Machine (LightGBM). An additional in-depth statistical analysis also revealed that the best beneficiaries of the policy intervention are those firms that experience performance issues in the period just before the interventions and for which the increased liquidity brought by the policy may have prevented default.
Association between exposure to ambient air pollution, meteorological factors and atopic dermatitis consultations in Singapore—a stratified nationwide time-series analysis
Authors: Mailepessov Diyar , Ong Janet , Nasir Muhammad Zafir Mohamad , Aik Joel , Woo Maye , Zhao Xiahong , Tey Hong Liang , Yew Yik Weng 
Published: May 2024

AbstractAtopic dermatitis (AD) is a chronic inflammatory skin disease affecting approximately 20% of children globally. While studies have been conducted elsewhere, air pollution and weather variability is not well studied in the tropics. This time-series study examines the association between air pollution and meteorological factors with the incidence of outpatient visits for AD obtained from the National Skin Centre (NSC) in Singapore. The total number of 1,440,844 consultation visits from the NSC from 2009 to 2019 was analysed. Using the distributed lag non-linear model and assuming a negative binomial distribution, the short-term temporal association between outpatient visits for AD and air quality and meteorological variability on a weekly time-scale were examined, while adjusting for long-term trends, seasonality and autocorrelation. The analysis was also stratified by gender and age to assess potential effect modification. The risk of AD consultation visits was 14% lower (RR10th percentile: 0.86, 95% CI 0.78–0.96) at the 10th percentile (11.9 µg/m3) of PM2.5 and 10% higher (RR90th percentile: 1.10, 95% CI 1.01–1.19) at the 90th percentile (24.4 µg/m3) compared to the median value (16.1 µg/m3). Similar results were observed for PM10 with lower risk at the 10th percentile and higher risk at the 90th percentile (RR10th percentile: 0.86, 95% CI 0.78–0.95, RR90th percentile: 1.10, 95% CI 1.01–1.19). For rainfall for values above the median, the risk of consultation visits was higher up to 7.4 mm in the PM2.5 model (RR74th percentile: 1.07, 95% CI 1.00–1.14) and up to 9 mm in the PM10 model (RR80th percentile: 1.12, 95% CI 1.00–1.25). This study found a close association between outpatient visits for AD with ambient particulate matter concentrations and rainfall. Seasonal variations in particulate matter and rainfall may be used to alert healthcare providers on the anticipated rise in AD cases and to time preventive measures to reduce the associated health burden.
Metacognition as a mediator of the relation between family SES and language and mathematical abilities in preschoolers
Authors: Maximino-Pinheiro Mélanie , Menu Iris , Boissin Esther , Brunet Lys-Andréa , Barone Carlo , Borst Grégoire 
Published: May 2024

AbstractThe effect of family socioeconomic status (SES) on academic achievement in literacy and numeracy has been extensively studied with educational inequalities already witnessed in preschoolers. This is presumably explained by the effect of family SES on cognitive and socioemotional abilities associated with academic achievement. Metacognition which refers to knowledge and regulation skills involving reflexivity about one's own cognitive processes is one of these abilities. However, most of the studies investigating the association between metacognition and academic achievement have focused on school-aged students and studies with younger students are only emerging. Meanwhile, the association between family SES and metacognition abilities has surprisingly received little attention regardless of participants’ age. The aim of this study was to explore the associations between family SES, metacognition, language and mathematical abilities in preschoolers aged 5 to 6. We provide the first evidence that the effect of family SES on preschoolers’ language and mathematical abilities is mediated by the effect of family SES on their metacognitive abilities. The implications for future research, education and policies aiming at reducing educational inequalities are discussed.
Experimental study on I/II/III mixed mode fracture characteristics of a combined rock mass under creep loading
Authors: Li Shuai , Zheng Chao , Li Peng , Zhang Shuo 
Published: May 2024

AbstractI/II/III mixed mode fractures of intersecting joint fissures often occur in natural rock masses, and jointed rock masses are prone to rockbursts in deep underground engineering when subjected to long-term crustal stresses. However, most studies of the mechanical mechanisms of these intersected joints have been conducted by simplifying two-dimensional joint model tests. Furthermore, the fracture mechanisms of two-dimensional intersected joints under tension and compression are completely different from those of three-dimensional joints. This paper presents a novel prefabricated specimen with combinations of intersecting joints capable of detecting the failure behaviours of rock I/II/III mixed mode fractures under creep loading. Uniaxial compression and multistage creep tests are performed on prefabricated sandstone specimens with intersecting joints of 0°/0°, 0°/30°, 0°/60°, and 0°/90°. The experimental results show that with the increase in the number of prefabricated intersecting joints, the uniaxial compressive strength and elastic modulus values of the sandstone specimens gradually decrease. In addition, the sandstone specimens experience relatively few AE events and minor axial strain variations in the first creep stage and the second creep stage of the multistage creep test. The axial strain increases sharply due to the sharp increase in the number of AE events in the third creep stage. The 0°/60° sandstone specimen undergoes accelerated creep failure, resulting in mixed X-shaped tensile‒shear rupture. The RA value is high based on the quantification of the creeping cracks using the acoustic emission parameters of the rise angle (RA) and average frequency (AF). The AF values of the 0°/0°, 0°/30°, and 0°/90° sandstone specimens are high. The experimental results show that a larger joint intersection angle leads to greater mutual restraints and greater effects of prefabricated crack propagation in the rock specimens, thus increasing the final failure strength. Finally, based on the acoustic emission count, a characteristic variable D suitable for characterizing the creep damage evolution of a joint rock mass is established. The findings of this paper can facilitate an effective understanding of the creep effect of I/II/III mixed mode fracture and its micromechanism. The research results will have a certain reference value for the detection and risk mitigation of instantaneous and time-delayed rockbursts.
Ferrocene probe-assisted fluorescence quenching of PEI-carbon dots for NO detection and the logic gates based sensing of NO enabled by trimodal detection
Authors: Priya S. , Berchmans Sheela 
Published: May 2024

AbstractOur research demonstrates the effectiveness of fluorescence quenching between polyethyleneimine functionalised carbon dots (PEI-CDs) and cyclodextrin encapsulated ferrocene for fluorogenic detection of nitric oxide (NO). We confirmed that ferrocene can be used as a NO probe by observing its ability to quench the fluorescence emitted from PEI-CDs, with NO concentrations ranging from 1 × 10–6 M to 5 × 10–4 M. The photoluminescence intensity (PL) of PEI-CDs decreased linearly, with a detection limit of 500 nM. Previous studies have shown that ferrocene is a selective probe for NO detection in biological systems by electrochemical and colorimetric methods. The addition of fluorogenic NO detection using ferrocene as a probe enables the development of a three-way sensor probe for NO. Furthermore, the triple mode NO detection (electrochemical, colorimetric, and fluorogenic) with ferrocene aids in processing sensing data in a controlled manner similar to Boolean logic operations. This work presents key findings on the mechanism of fluorescence quenching between ferrocene hyponitrite intermediate and PEI-CDs, the potential of using ferrocene for triple channel NO detection as a single molecular entity, and the application of logic gates for NO sensing.
Max-mixed EWMA control chart for joint monitoring of mean and variance: an application to yogurt packing process
Authors: Malik Seher , Hanif Muhammad , Noor-ul-Amin Muhammad , Khan Imad , Ahmad Bakhtiyar , Abaker Abdelgalal O. I. , Ahmed Darwish Jumanah 
Published: May 2024

AbstractThe Max-Mixed EWMA Exponentially Weighted Moving Average (MM EWMA) control chart is a statistical process control technique used for joint monitoring of the mean and variance of a process. This control chart is designed to detect small and moderate shifts in the mean and variance of a process by comparing the maximum of two statistics, one based on the mean and the other on the variance. In this paper, we propose a new MM EWMA control chart. The proposed chart is compared with existing control charts using simulation studies, and the results show that the chart performs better in detecting small and moderate shifts in both the mean and variance. The proposed chart can be helpful in quality control applications, where joint monitoring of mean and variance is necessary to ensure a product’s or process’s quality. The real-life application of the proposed control chart on yogurt packing in a cup data set shows the outperformance of the MM EWMA control chart. Both simulations & real-life application results demonstrate the better performance of the proposed chart in detecting smaller shifts during the production process.