bluuebunny/crossref_metadata_2025 huggingface dataset:
A Classification Approach of Conglomerate Reservoirs Considering the Effects of Reservoir Simulation: A Case Study in Triassic Baikouquan Formation, North Slope of Mahu Depression
Authors: Li Xiangyang , Ji Hancheng , Li Fengxia , Wang Haibo , Chen Liang , Huang Zhiwen , Zhang Zhonghao , Shi Xukai
Published: February 2024

The 1Gt oil field's finding has solidified the Mahu oil Field's status, the largest conglomerate oil region in the world, and demonstrated the enormous exploration potential of conglomerate reservoirs. Optimizing and selecting the target interval during hydraulic fracturing is challenging due to the significant heterogeneity of the conglomerate reservoir. Based on issues encountered in the actual production of oil and gas from conglomerate reservoirs of the Baikouquan Formation (T1b), north slope of Mahu Depression, the composition of gravel was examined and analyzed in this paper. A novel classification approach is developed considering the structural and compositional features of the conglomerate reservoir in the T1b. Taking into account the grain size, supporting forms, cementation degree, and compositional properties, the conglomerate of the T1b is categorized into two groups and eight subcategories based on the core and test results. The conglomerates of T1b were initially divided into fan delta front and plain conglomerates according to the type of genesis. Fan delta front conglomerates were divided into four types: tuff, metamorphic rocks and magmatic rocks-dominated gravel-supported cobble-to-boulder lithofacies (A-1); tuff and magmatic rocks-dominated matrix-supported pebble-to-cobble lithofacies (A-2); tuff-dominated matrix-supported granule-to-pebble lithofacies (A-3); and tuff-dominated gravel-supported granule-to-pebble lithofacies (A-4). Fan delta plain conglomerates were divided into four types: tuff and magmatic rocks-dominated gravel-supported granule-to-pebble lithofacies (B-1); tuff and sedimentary rocks-dominated gravel-supported pebble-to-cobble lithofacies (B-2); tuff-dominated gravel-supported cobble-to-boulder lithofacies (B-3); tuff, magmatic rocks and sedimentary rocks-dominated matrix-supported pebble-to-cobble lithofacies (B-4). The sedimentary structure, bedding, lithofacies association, composition, grain size, and poroperm characteristics of the different conglomerate lithofacies are investigated. The favorable lithofacies types have been evaluated from both the geological and engineering perspectives. The insight of this paper is expected to provide some references for oil and gas exploration and development, as well as the selection of favorable lithofacies for hydraulic fracturing of conglomerate reservoirs.
Regulation of soil-plant nitrogen dynamics by (in)organic nitrogen sources with and without biostimulant for sustainable maize (Zea mays L.) production in nitrogen-deficient soil
Authors: Bibi Hamida , Rahim Hafeez , Shams Dilawar Farhan , Nawaz Muhammad , Iqbal Mudassar , Azeem Imran , Baig Shams Ali
Published: February 2024

Nitrogen deficiency is a primary factor contributing to reduced crop production in arid and semiarid regions. Addressing this issue requires optimizing soil-plant nitrogen dynamics. In this field experiment, we investigated the impact of organic (farmyard manure) and inorganic (urea) nitrogen sources, both with and without biostimulant (Bioaab), on soil-plant nitrogen dynamics and sustainable maize (Zea mays L.) production in nitrogen-deficient soil. Five different combinations of farmyard manure (FYM) and urea—0:100, 25:75, 50:50, 75:25, and 100:0—were developed and applied with and without Bioaab in a randomized complete block design with a factorial arrangement in triplicate. Organic (FYM) and inorganic (urea) nitrogen sources, whether combined with Bioaab or not, significantly (p < 0.05) improved soil-plant nitrogen content and maize yield. The addition of FYM, whether Bioaab was present or not, had no significant (p > 0.05) impact on yield parameters. In contrast, the application of Bioaab enhanced soil-plant nitrogen dynamics, as indicated by increased plant total nitrogen (1.37%) and total nitrogen uptake (95.7 kg ha− 1) by maize plants, resulting in significantly higher yield compared to non-Bioaab treated plots. However, non-Bioaab treated pots surprisingly recorded maximum soil total nitrogen content (0.057%). Moreover, the plot treated with Bioaab recorded the maximum biomass production (7.99 tons ha− 1), number of grains (2.873 tons ha− 1), and soil organic matter content (1.20%). In conclusion, the use of inorganic fertilizer with a biostimulant (Bioaab) is crucial for improving crop yield and nitrogen release.
High-Pressure Ultrafast Time-Resolved Far-Infrared Full-spectrum Spectroscopy with Air-Based Upconversion
Authors: Yang Yanqiang , Zhu Gangbei , Zeng Yangyang , Mu Jian , Zheng Zhaoyang , Yu Guoyang
Published: February 2024

Most condensed materials exhibit characteristic excitations in the far-infrared range. The ultrafast dynamics of these excitations significantly influence the fundamental physical and chemical properties of the materials. Moreover, modulating the dynamics of these excitations through pressure variations is intriguing for unveiling the key microphysical processes involved and can offer dynamic experimental support for exploring novel materials. In this study, we demonstrate the first experimental elucidation and application of ultrafast time-resolved far-infrared full-spectrum spectroscopy combined with high-pressure diamond anvil cell (DAC) technology. The combination of an air-plasmon-based continuum and an air-based single-shot upconversion detection technique have been first employed in high-pressure time-resolved infrared spectroscopy. The air-plasmon-based ultrabroadband far-infrared continuum was directed into a DAC and the transmitted pulse was detected in a single shot form through four-wave mixing in the air to avoid the absorptions from phonon modes of the nonlinear medium. It allows the real-time capture of the spectrum spanning from < 50 to > 1800 cm− 1, with a few-cm− 1 spectral resolution. We investigate the pressure-dependent vibrational coupling dynamics of the complete set of vibrational fingerprint modes in microcrystalline octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) following mode-selective vibrational mode excitation. The results reveal that pressure enhances the vibrational coupling and energy transfer between the excited vibrational modes and doorway modes. The combination of high-pressure technology and time-resolved full-spectrum infrared spectroscopy opens up new perspectives for the study of the ultrafast phenomena in material science.
Role of Small Bowel Capsule Endoscopy in Determining the Treatment Strategy for Duodenal Follicular Lymphoma: A Single-Center Retrospective Study
Authors: Kang Donghoon , Min Gi-June , Kim Tong Yoon , Jeon Young-Woo , Cho Yukyung , Park Jae Myung , O Joo Hyun , Choi Byung-Ock , Park Gyeongsin , Cho Seok-Goo
Published: February 2024

In this single-center retrospective study, we aimed to verify the extent of duodenal follicular lymphoma (DFL) and investigate the role and clinical significance of video capsule endoscopy (VCE) in this process. We analyzed the clinical and imaging data of 40 patients diagnosed with DFL. Imaging workup and bone marrow biopsies revealed DFL only in the gastrointestinal tract (stage I) in 22 patients and in local lymph nodes (stage II1), distant lymph nodes (stage II2), pancreas (stage II2Epancreas), and extranodal regions (stage IV) in 1, 3, 1, and 13 patients, respectively. Fifteen of the 23 patients with localized (stages I and II1) DFL underwent VCE for comprehensive small bowel evaluation, which revealed lesion extension beyond the duodenum in 10 patients (66.7%). A watch-and-wait strategy was implemented for 1 patient and systemic chemotherapy was administered to the remaining nine. Of the eight patients without VCE, seven and one received radiotherapy and observation, respectively. Nine of the 23 patients (39.1%) received systemic treatment based on positive VCE results. Only one of the 17 patients with advanced-stage DFL (stages II2 and IV) accepted radiotherapy; 16 underwent systemic chemotherapy. During follow-up (median, 48.4 months), two relapse events occurred in the advanced stage, with no lymphoma-associated deaths. DFL tends to be indolent with favorable outcomes. Proactive VCE for diagnosing DFL is recommended to determine small bowel involvement, which may influence subsequent treatment decisions.
Effect of waste fly ash incorporated into the polymer matrix and surface interactions on radiation shielding effectiveness
Authors: Özcan Mücahid
Published: February 2024

This study focuses on enhancing the surface modification of waste fly ash, which is generated by coal combustion in thermal power plants. The electrospinning method was used to reinforce waste fly ash onto PAN nanofiber. The present study investigates the surface interaction between ceramic fly ash particles and PAN polymer and the potential synergy that may arise from their combination. The flexing capacity of PAN fiber has been found to reach up to three times its original size while simultaneously integrating the fly ash ceramic component into its structural composition. It has been discovered that adding fly ash to PAN Fiber improves its gamma and neutron shielding properties. According to this understanding, the radiation at 0.05 MeV energy can be reduced by 50% with just 0.7 cm of fly ash-reinforced PAN nanofiber material.
EvoAI enables extreme compression and reconstruction of the protein sequence space
Authors: Zhang Shuyi , Ma Ziyuan , Li Wenjie , Shen Yunhao , Xu Yunxin , Liu Gengjiang , Chang Jiamin , Li Zeju , Qin Hong , Tian Boxue , Gong Haipeng , Liu David , Thuronyi B , Voigt Christopher
Published: February 2024

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here, we first establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.
Poly(2-vinylpyridine) magnetite nanoparticles for 5-fluorouracil targeted delivery: synthesis, uptake and release study
Authors: Korolkov I. V. , Izbasar K. A. , Bekbol Zh. A. , Zibert A. V. , Shumskaya A. E. , Lissovskaya L. I. , Korganbayeva L.N. , Zdorovets M. V.
Published: February 2024

One of the major limitations of anti-cancer drug is their poor selectivity and high toxicity. Present study is aimed overcoming these difficulties by development targeted drug delivery systems. Drug delivery systems were synthesized based on magnetite nanoparticles with grafted poly(2-vinylpyridine) from their pre-modified surface with 3-(trimethoxysilyl)propyl methacrylate. Physical and chemical properties of synthesized samples were examined by FTIR, XRD, VSM, EDA, Mössbauer spectroscopy. 5-FU release from nanocarriers was estimated using UV-Vis spectroscopy.
An evaluation of the effectiveness of an updated pre-service midwifery curriculum integrated with emergency obstetrics and newborn care in Kenya: a cluster randomised controlled trial
Authors: Shikuku Duncan N , Mwaura Catherine , Nandikove Peter , Uyara Alphonce , Allott Helen , Waweru Lucy , Nyaga Lucy , Tallam Edna , Bashir Issak , Ndirangu Eunice , Bedwell Carol , Bar-Zeev Sarah , Ameh Charles
Published: February 2024

Introduction
Quality midwifery education is central to improving midwifery service delivery and maternal and newborn health outcomes. In many settings, midwifery educators insufficiently prepared for their teaching role and deficient curriculum compared to international standards affect the quality of midwifery graduates. This study assessed the effectiveness of an EmONC enhanced midwifery curriculum delivered by trained and mentored midwifery educators on the quality of education and student performance in Kenya.
Methods
A cluster randomised controlled trial (ISRCTN 14203188) in 20 midwifery colleges (12 intervention and 8 control colleges). Educators in both arms received training in teaching/EmONC skills to deliver the updated national midwifery curriculum, with those in the intervention arm receiving additional mentoring every three months after training for 12 months. Educators’ knowledge and confidence in EmONC/teaching skills was assessed before and after training and at 3, 6, 9 and 12 months. Teaching skills observations at baseline and endline in both study arms were also assessed using a checklist. Knowledge, confidence and three selected EmONC practical skills among final year midwifery students were assessed. Linear mixed effects models were used to evaluate the effect of intervention on educators and students.
Results
The intervention arm had 45 educators and 91 students while the control arm had 29 educators and 55 students in the study. Immediately after training educators’ knowledge improved (61.3–73.3%, p < 0.001) and confidence to teach EmONC (3.1 to 4.2 out of 5, p < 0.001) improved. No evidence of a difference in either knowledge or confidence was detected for period or study arm (p > 0.05). The observed teaching skill scores of educators in the intervention arm were significantly higher compared with those of controls at endline (mean difference, 16.5; 95%CI, 3.2–29.8, p = 0.02). Scores for students in the intervention arm were significantly higher than those in controls for knowledge (mean difference, 8.3 [1.6–15.0]) and the three skills assessed (mean difference (95%CI): 22.4 (10.8–33.9) for shoulder dystocia, 17.9 (2.0-33.9) for newborn resuscitation and 17.0 (8.0–26.0) for maternal resuscitation. Shortage of faculty and inadequate support in clinical placement were major challenges for quality midwifery education.
Conclusion
Knowledge and confidence of educators in teaching EmONC was improved immediately after training. Mentoring was effective in improving the quality of educators’ EmONC teaching skills. Students in intervention arm had higher performance in EmONC knowledge and skills. Institutional investments are needed for quality delivery of an EmONC-enhanced curriculum.
Effects of woodland slope on heavy metal migration via surface runoff, interflow, and sediments and associated potential ecological risks following the application of sewage sludge
Authors: Xian Lihua , Lu Dehao , Yang Yuantong , Feng Jiayi , Fang Jianbo , Jacobs Douglass F. , Wu Daoming , Zeng Shucai
Published: February 2024

The application of sewage sludge (SS) to woodland is an effective approach for the disposal and utilization of SS. However, the woodland slope may determine the risk of heavy metal (HM) migration via runoff. We conducted indoor rainfall simulations and natural rainfall experiments to clarify the effect of slope on the migration of HMs via runoff (including surface and interflow) and sediments. In the simulated rainfall experiment, HMs lost via sediments increased by 9.79–27.28% when the slope increased from 5° to 25°. However, in the natural rainfall experiment, when the slope of forested land increased from 7° to 23°, HMs lost via surface runoff increased by 2.38% to 6.13%. It revealed that the surface runoff water on a high slope (25°) posed high water quality pollution risks. The migration of HMs via surface runoff water or interflow increased as the steepness of the slope increased. The total migration of Cu, Zn, Pb, Ni, Cr and Cd via sediment greatly exceeded that via surface runoff and interflow. Particles ≤0.05 mm contributed the most to the ecological risks posed by sediments. Cd was the main source of potential ecological risks in sediments under both experimental conditions.
Research on the aggregation phenomena in moraine soil: a new approach to disperse them through a particle size analysis
Authors: Lu Tuo , Tie Yongbo , Tang Yaming , Ning Zhijie , Gong Lingfeng
Published: February 2024

Moraine soils exposed to the moraine landscape surface due to glaciers retreating and global warming have been the subject of interest for researchers. The particle size distribution (PSD) of moraine soils is essential to understanding their engineering properties and soil characteristics. However, the wide aggregation phenomena observed in these soils introduce difficulties in particle size analysis. To overcome this, an experimental group test (EGT) and control groups test (CGT) were designed, which included a series of pretreatment methods to disperse particles, such as grain sieving test, laser diffraction test, microscopic observation, and scanning electron microscope. The tests were performed to record the aggregation phenomena and perform particle size test analysis. The results revealed widespread evidence of aggregation phenomena in each grain group (ranging from < 0.075 mm to 60 mm ~ 40 mm), encapsulated by three basic conceptual models (Core-coating, Core(s)-coat, and Coat-coring) for moraine soil. A new pretreatment method was developed, which involved the addition of 0.5% polycarboxylate in optimal ultrasonic dispersion to disperse aggregation phenomena before the sieving and laser diffraction tests. This method proved to be effective in removing the aggregation phenomena, which significantly impacted on the particle size distribution of moraine soils. The aggregation phenomena caused an overestimation of the content of the gravel group (about 7.91%) and an underestimation of the content of the silt-clay group (about 5.07%). After effectively removing the aggregation phenomena, many samples collected from poorly graded gravelly soils (GP) became silty sand soil (SM) and silty gravel soil (GM). Additionally, the average particle size was reduced by approximately 40%.
Computational Analysis of Bulb-Shape Ribs Roughened Absorber Plate of Solar Air Heater
Authors: Mor Swati , Sikarwar Basant Singh , Kumar Niraj , Gautam sachin Singh
Published: February 2024

In this work, thermo-hydrodynamic simulation was carried out for bulb-shaped ribs roughened absorbing surface of solar air heater at 1kW/m2 for and various Reynolds numbers. Primarily, sensitivity analysis of turbulent models was carried for flow over the surface, and it observed that RNG k-\(\epsilon\) model results is more closed with respect to Dittus-Boelter equation. After selection of appropriate turbulence model, simulations were carried out on a bulb-shape rib and other shapes of roughened ribs surface. This study reveals that absorber bulb shaped ribs roughened surface has at least two times more performance improvement factor (Nu/f) as compared to the other ribbed shape roughened surface. Eventually, the Nusselt number and Coefficient friction for bulb shaped ribs roughened surface were correlated in terms of Reynolds number (Re) and relative roughness (β). These correlations are substantial for designing solar air heating systems for bulb-shaped ribs roughened as absorbing surface.
Exosomes derived from microRNA-22-3p-overexpressed mesenchymal stem cells protect retinal ganglion cells by regulating MAPK pathway
Authors: Zhang Xiaomin , Yu Bo , Wang Kang , Hao Huijie , Liu Yan , Yue Yi , Li Xiaorong , Xing Xiaoli
Published: February 2024

Glaucoma is the leading cause of irreversible blindness and is characterized by progressive retinal ganglion cell (RGC) loss and retinal nerve fiber layer thinning. Currently, no existing treatment is effective for the preservation of RGCs. MicroRNA-22-3p (miR22) and exosomes derived from mesenchymal stem cells (MSC-Exos) have neuroprotective effects. In this study, we applied miR22-overexpressing MSC-Exos in an N-methyl-D-aspartic acid (NMDA)-induced RGC injury model to assess their therapeutic effects and explore the underlying mechanisms. We found that mice in the miR22-Exos-treated group had thicker retinas, fewer apoptotic cells, more reserved RGCs, better retinal function, and lower expression levels of caspase-3. MiR22-Exos treatment promoted proliferation, and inhibited apoptosis and caspase-3 expression in RGC-5 cells. MiR22 targeted mitogen-activated protein kinase kinase kinase 12 to inhibit apoptosis by regulating the mitogen-activated protein kinase (MAPK) signaling pathway. Collectively, our results suggest that miR22-Exos ameliorate NMDA-induced RGC injury through the inhibition of MAPK signaling pathway-mediated apoptosis, providing a potential therapy for glaucoma and other diseases that involve RGC damage.
Improvement of the crystalline silicon photovoltaic cell performances under electromagnetic field by base doping level
Authors: OUEDRAOGO Adama , SAWADOGO Rodrigue Noaga , DIANDA Boureima , SAVADOGO Mahamadi , KY Thierry Maurice Sikoudouin , SORO Boubacar , BATHIEBO Dieudonné Joseph , KAM Sie
Published: February 2024

The present paper provides a study about the capacity of a crystalline silicon photovoltaic (PV) cell to resist well to electromagnetic field effects. The novelty of this study is found in the identification of a better doping rates range where a crystalline silicon PV cell can resist well against the deterioration of its performances due to an electromagnetic field. After the fundamental equations solve, the electrical parameters and individual energetic processes have been analysed. The estimated current of the PV cell decreases weakly when the base dopant level (N B) increase from 10 14 cm −3 to 10 17 cm −3 and the voltage, however, increases strongly. Beyond 10 17 cm −3 , the currents gives a strong decrease in contrast the voltage which provides a low increase. That can be explained by a best resistivity to the electromagnetic field found at 10 17 cm −3 and is consistent with the maximum electric power found in this doping level. Thermalization mechanism does not affected by the electromagnetic field and doping rate. But the analyses of the thermodynamic process behaviour and fill factor on the one hand and on the other hand the behaviour of the absorption mechanism, show that the best capability resistivity to the electromagnetic field is found at 10 17 cm −3. Hence the base doping in boron level can be used to improve the electromagnetic resistivity of the PV cell in crystalline silicon with a well control of the Light-Induced Degradation (LID).
Generation of realistic synthetic cable images to train Deep Learning segmentation models
Authors: Fresnillo Pablo Malvido , Mohammed Wael M. , Vasudevan Saigopal , Garcia Jose A. Perez , Lastra Jose L. Martinez
Published: February 2024

One of the main contemporary challenges in robotics is the automation of tasks that involve handling Deformable Linear Objects (DLOs), such as cables or ropes. Due to their changing shape, constant perception is required, which makes computer vision, and in particular, image segmentation, fundamental. Even though image segmentation is a very studied problem, which has been addressed with high accuracy by many different Deep Learning models, they need to be properly trained to segment the objects of interest (DLOs in this case). To do this, it is necessary to have a large and diverse dataset. However, such a dataset hasn’t been created for cable images, and doing it manually would be complicated and extremely time-consuming. This paper addresses this issue with a novel methodology, which automatically generates synthetic cable datasets to train image segmentation models. This methodology utilizes Blender to create photo-realistic scenes and a Python pipeline to interact with them. To ensure the diversity of the dataset, before the generation of each image, the pipeline performs random variations on the elements of the scene. After this, the scene is animated, dropping the cables from a certain height and letting them deform naturally after landing, which results in realistic arrangements of the cables. The effectiveness of the methodology was demonstrated by training six popular segmentation models with synthetic datasets and using them to segment real cable images with great results (IoU over 70% and Dice coefficient over 80% for all the models).
ESC-Net: Overcoming language priors in VQA via enhancing visual feature
Authors: Chowdhury Souvik , Soni Badal
Published: February 2024

Most current times Visual Question Answering (VQA) models fail to interpret the multimodal knowledge of visual and text simultaneously leading to language prior problem. Language prior or language bias is a scenario where a model is biased towards the question and provides answer favouring most frequent related answer. In this scenario, model ignores the visual features. In order to reduce language prior, researchers have proposed ensemble methods (combining multiple models each serves different purpose), balanced data methods (generating additional data), modified evaluation strategy (mostly towards giving higher penalty to biased answers during training to reduce the effects) or a modified training framework (different training approaches for biased and unbiased samples). The ensemble methods suffer reduction in performance accuracy, data balance methods generate additional bias, evaluation methods does not work as intended because of random frequency distribution of related answers, modified training framework adds complexity thus it has to segregate between biased and unbiased samples. In this paper, we propose a VQA model "Ensemble of Spatial and Channel Attention Network (ESC-Net)" to overcome language bias problem by improving the visual features. In this work, we have considered a blended approach of using both regional and global image features and using an ensemble of combined channel and spatial attention mechanism to improve visual feature. The model is a more simple and effective solution than existing methods to solve language bias. Extensive experiment shows a remarkable performance improvement of 18% on VQACP v2 dataset with a comparison to current state-of-the-art (SOTA) models.
A 20-year time-series of a freshwater lake reveals seasonal dynamics and environmental drivers of viral diversity, ecology, and evolution
Authors: Anantharaman Karthik , Zhou Zhichao , Tran Patricia , Martin Cody , Rohwer Robin , Baker Brett , McMahon Katherine
Published: February 2024

Long-term ecological studies are powerful tools to investigate microbiomes and ecosystem change but have mostly ignored viruses. Here, we leveraged a 20-year time-series of a freshwater lake to characterize 1.3 million viral genomes over time, seasonality, and environmental factors. We identified 578 auxiliary metabolic gene (AMG) clusters representing over 150,000 AMGs, the most abundant of which, including psbA for photosynthesis, pmoC for methane oxidation, and katG for hydrogen peroxide decomposition, were consistently represented in viruses across decades and seasons. We observed positive associations and niche differentiation between virus-host pairs during seasonal change including in keystone taxa, Cyanobacteria, methanotrophs, and Nanopelagicales. Environmental constraints, specifically inorganic carbon and ammonium influenced viral abundances over time, and highlighted roles of viruses in both “top-down” and “bottom-up” interactions. Key evolutionary processes shaping gene and genome-wide selection included favored fitness genes, reduced genomic heterogeneity, and dominant sub-populations carrying specific genes. Overall, our study advances understanding of diversity, ecological dynamics, and evolutionary trajectories of viruses in Earth’s microbiomes and ecosystems.
Metabolomic Profiling of in vitro and in situ Grown Nilgiris Tea Unraveled Unique Signatures of Caffeine Related Metabolites
Authors: M Rishikesh , Boopathi Manikanda , M Raveendran , P Meenakshisundaram , S Varanavasiappan , Premnath Ameena , G Shobhana V , P Santhanakrishnan V , Lourdusamy Keiser , M Kannan
Published: February 2024

In this study, UPASI 9, a Nilgiris tea clone (Camellia sinensis), commonly cultivated using environmentally harmful and economically impractical cutting methods, has been reconsidered for propagation through a more sustainable approach using tissue culture. It was begun by establishing an in vitro culture and optimizing various factors such as explant source materials, disinfection procedures, and the composition of the culture medium. Anatomical studies demonstrated that the use of lower carbendazim concentration for sterilization (0.2%) produced viable and healthy explants for callus initiation, which is a key limiting factor in the success of tea tissue culture. To confirm the genetic consistency of the regenerated plants, gene-specific SSR markers were developed and utilized to ensure that the proliferated callus preserved the same genetic characteristics as that of the mother plants. Gas chromatography-mass spectrometry (GC-MS) was employed to analyze volatile metabolites extracted from callus, stem, micro shoots, and leaves of the UPASI 9 tea genotype. The results revealed distinct compositions of metabolites in each sample: callus showed unique metabolites like keto acids and derivatives, organic sulfonic acids, and their derivatives, and oxanes. Leaves stood out with imidazopyrimidines and prenol lipids, micro shoots with purine nucleotides and sulfinic acids, and stems with indoles and derivatives, pyrans, and tetrazines. However, eight classes of metabolites were consistently present in all four UPASI 9 samples. More interestingly, caffeine was exclusively detected in leaf samples but absent in all other investigated tissues, despite the presence of Tea Caffeine Synthase (TCS) gene-specific SSRs. Thus, this study provided unique information on the absence of caffeine in the in vitro grown Nilgiris tea clone, UPASI 9, which can be utilized further to create a decaffeinated tea product with minimal cost that has a unique demand in the global market.
The state of the AMOC revealed from the Subpolar North Atlantic Sea Surface Salinity
Authors: Xu Fanghua , Dai Jinhui , Wright Jonathon S.
Published: February 2024

As a critical regulator of the global climate system, the Atlantic Meridional Overturning Circulation (AMOC) has attracted huge attention since its bimodal state change could abruptly alter climate1–5. The subpolar sea surface temperature (SST) has been used as a fingerprint to predict the state change of AMOC3,6–8. Although the subpolar SST agrees well with the variability of AMOC in recent years, it is under debate whether the subpolar SST can represent the abrupt state change of AMOC since its physical role remains unclear9. In contrast, it is well-known that the freshwater flux in high latitudes is a key to AMOC stability10–13. To foresee the AMOC collapse based on salinity, we investigate the relationship of SST and SSS with various AMOC mean states from the Paleoclimate Modeling Intercomparison Project phase 4 (PMIP4). It is found that SST does not agree with changes in AMOC mean state under various climate conditions, while the sea surface salinity (SSS) within the subpolar North Atlantic (SPNA) does. Our results indicate that about 3.5 PSU drop in SPNA SSS is required for AMOC collapse to totally shut down. It's worth noting that no significant salinity trend was observed in the SPNA, implying the stability of deep water formation in recent decades. More attention should be paid to monitoring salinity variations in the SPNA and studying the anthropogenic-induced ice melting and alterations in the water cycle in high latitudes.
Differences in COVID-19 vaccine hesitancy and trusted sources of information among a large sample of Chicagoans
Authors: Jacobs Jacquelyn , Hasan Noor , Bishop-Royse Jessi , Camargo Lucky , Roberson Alyce
Published: February 2024

Evidence shows that vaccine hesitancy is associated with lower rates of vaccine uptake. Vaccine hesitancy is driven by many factors related to individual belief and experience, and has increased since the start of the COVID-19 pandemic. Surveillance data shows there has been lower vaccine uptake within Black and Brown communities across the United States, which can lead to increased transmission and costs to the community. This study analyzed data from a pulse survey disseminated across Chicagoland to collect data on perceptions of COVID-19 and vaccination. Responses related to vaccine status, attitudes and beliefs, trusted sources, and sociodemographic characteristics were examined. Descriptive and bivariate analyses were conducted to characterize the sample and examine unadjusted relationships. Multivariate regression was used to estimate factors associated with vaccination. Respondents (n = 1430) were primarily female (67.3%), over 30 (69.7%), and Hispanic/Latino (38.5%) or non-Hispanic Black (38.3%). Most respondents were vaccinated (84.8%) at the time of the survey. Compared to unvaccinated participants, vaccinated participants were less likely to believe that the vaccine was developed too quickly (45% and 56%, respectively). Respondents reported high levels of trust in their doctors, pharmacists, and in the Centers for Disease Control (79.7%, 74.0%, and 72.9%, respectively). Participants believing that the vaccine is safe and effective were more likely to have received the vaccine (OR = 14.0 and 11.74, respectively). Beliefs, attitudes, and knowledge around COVID-19 vaccination is significantly associated with vaccine uptake. These findings are particularly important in minoritized communities where low vaccine uptake has had adverse health outcomes.
Scale up of COVID-19 testing services in NYC, 2020-2021:
Lessons Learned to Maximize Reach, Equity and Timeliness
Authors: Thorpe Lorna , Conderino Sarah , Bendik Stefanie , Berry Carolyn , Islam Nadia , Masser Rachel , Chau Michelle , Larson Rita , Paul Margaret , Hong Chuan , Fair Andrew , Titus Andrea , Bershteyn Anna , Wallach Andrew
Published: February 2024

During infectious disease epidemics, accurate diagnostic testing is key to rapidly identify and treat cases, and mitigate transmission. When a novel pathogen is involved, building testing capacity and scaling testing services at the local level can present major challenges to healthcare systems, public health agencies and laboratories. This mixed methods study examined lessons learned from the scale-up of SARS CoV-2 testing services in New York City (NYC), as a core part of NYC’s Test & Trace program. Using quantitative and geospatial analyses, the authors assessed program success at maximizing reach, equity and timeliness of SARS CoV-2 diagnostic testing services across NYC neighborhoods. Qualitative analysis of key informant interviews elucidated key decisions, facilitators and barriers involved in the scale-up of SARS-CoV-2 testing services. A major early facilitator was the ability to establish working relationships with private sector vendors and contractors to rapidly procure and manufacture necessary supplies locally. NYC residents were, on average, less than 25 minutes away from free SARS CoV-2 diagnostic testing services by public transport, and services were successfully directed to most neighborhoods with highest transmission rates, with only one notable exception. A key feature was to direct mobile testing vans and rapid antigen testing services to areas based on real-time neighborhood transmission data. Municipal leaders should prioritize fortifying supply chains, establish cross-sectoral partnerships to support and extend testing services, plan for continuous testing and validation of assays, ensure open communication feedback loops with CBO partners, and maintain infrastructure to support mobile services during infectious disease emergencies.
Prevalence of hyperuricemia and its correlation with metabolic syndrome in young adults: a cross-sectional study in eastern China
Authors: Lu Bohan , Hu Cuirong , Lu Jifang , Wang Jinkun , Jin Haijiao , Wang Ling , Gu Leyi , Ni Zhaohui , Mou Shan , Jiang Na
Published: February 2024

Background
Hyperuricemia (HUA) has emerged as a significant metabolic disease, particularly in young population with metabolic syndrome (MS). The purpose of this study was to study the prevalence of HUA and its correlation with metabolic syndrome among young adults in a coastal city of eastern China.
Methods
It was a cross-sectional study conducted in adults undergoing routine healthy checkup. Anthropometric data and serological parameters were collected and in related to serum uric acid (SUA) concentration and prevalence of HUA.
Results
A total of 9,196 adults with mean age of 34.3 ± 11.8 years old and 75.2% of males were recruited. Mean SUA level was 371.8 ± 95.6 µmol/l and overall HUA prevalence was 31.3%. SUA level was higher and HUA was more common in younger males, as well as in those with MS (OR: 3.07; 95% CI: 2.78–3.39) demonstrated by using the univariable binary logistic regression analysis model. The multivariable binary logistic regression analysis revealed that male (OR: 3.74; 95% CI: 3.12–4.48), young age (OR: 1.22; 95% CI: 1.19–1.26), low estimated-glomerular filtration rate (OR: 2.45; 95% CI: 2.11–2.84), high body mass index (OR: 2.31; 95%CI: 2.06–2.60), hypertension (OR: 1.18; 95% CI: 1.04–1.32), high serum triglyceride (OR: 2.08; 95%CI: 1.81–2.37), and low serum high-density lipoprotein cholesterol (OR: 1.33; 95% CI: 1.15–1.55) were independent risk factors associated with HUA prevalence.
Conclusion
SUA level increased and HUA was common in young adults. Male, young age, reduced kidney function, combined with MS and more MS components were associated with prevalence of HUA.
A systematic design approach for a novel energy efficient ALU for 8-bit QCA microcontroller
Authors: karuppiah pandiammal , Deivasigamani Meganathan
Published: February 2024

Quantum Cellular Automata (QCA) provide a new computing paradigm to implement the high speed digital architecture at nano-scale with low power consumption. The design of an 8-bit arithmetic logic unit (ALU) for microcontroller using QCA technology is the most challenging and has not been addressed so far. In this paper, we propose a systematic design approach for the design of novel energy-efficient 8-bit ALUs for scalar microcontrollers using QCADesigner. The proposed eight-bit ALU uses 24.25 (10-1ns) clock delay, occupies 198.48 µm2 area, and dissipates 15.5 eV of energy.
A Retrospective Review of Dissection Type and Outcomes in Advanced Glottic Carcinoma
Authors: Soon Stephanie , Habib Ayaaz , Wong Winson , Jose Jemy
Published: February 2024

Intro:
Neck dissection is performed in the management of advanced laryngeal carcinoma due to the risk of metastases to cervical lymphatics. Current NCCN Guidelines and UK guidelines offer differing advice on glottic carcinoma, with NCCN recommending ipsilateral and/or bilateral dissection and UK recommending bilateral dissection. This paper aims to assess the outcomes of unilateral and bilateral neck dissection in surgically managed advanced glottic carcinoma.
Method:
Retrospective review of twenty-four patients with advanced glottic carcinoma (T3-4, N-N2b) from the years 2014-2020 who had as primary surgical treatment. Survival analysis, cox regression and fisher exact test were performed.
Results:
We found no statistically significant difference in 5-year overall survival and local recurrence between unilateral neck (ULN) dissection and bilateral neck dissection (BLN).
Conclusion:
While the data from this study shows no statistical significance between dissection type and survival, we suggest that ULN, based on published literature provides an equivalent survival outcome with a lower complication rate.
Investigating Natural Convection Heat Transfer in a Triangular Enclosure with Rectangular Finned Arrays Using Machine Learning: A Comparative Study of Support Vector Regression and Extreme Learning Machines
Authors: Das Debasish , Kaul Vishesh , Pandita Saubhagya , Kankipati Noel
Published: February 2024

In this research study, Support Vector Regression (SVR) and Extreme Learning Machines (ELM) are harnessed as powerful machine learning techniques to enhance the precision of predicting the Nusselt number. The primary objective is to utilise these models for estimating the maximum natural convection heat transfer within a triangular enclosure featuring an in-line rectangular finned array. The investigation delves into the impact of two critical factors, fin spacing (S) and applied voltage (V), with the ultimate goal of optimising these parameters to maximise heat transfer, quantified by the Nusselt number. The study presents a comparative analysis of the predictive capabilities of SVR and ELM when applied to experimental data. R-squared values for each machine-learning model are scrutinised through rigorous examination, providing insights into their suitability for predicting experimental outcomes with minimal error. This research contributes to understanding how machine-learning paradigms can be effectively employed in optimising heat transfer processes, offering valuable implications for applications in diverse fields such as thermal engineering and heat transfer enhancement.
Synthesis, Structure, Morphology, Dielectric, and Optical Properties of LaSrZrFeO6 : A Novel A-Site and B-Site Disordered Double Perovskite
Authors: Boudad Lahcen , Taibi M'hamed , Boukili Abdellah El , Belayachi Azzam , ABD-LEFDIL Mohammed
Published: February 2024

The LaSrZrFeO6 powder was synthesized using a conventional solid-state reaction process. The qualitative phase analysis through X-ray Diffraction (XRD) and data analysis with Rietveld refinement confirm the single-phase formation of a novel double perovskite. Crystal structure investigation was conducted to determine the lattice parameters, bond lengths, angles, and ions distribution. Additionally, crystallite size, lattice strain, density, and porosity were calculated. Fourier-transform infrared (FTIR) spectroscopy has been performed to examine the vibrational modes and bond formations in the sample. The sample's microstructure, including grain shape and size distribution, and elemental composition, were assessed using Field Emission Scanning Electron Microscopy (FE-SEM) and Energy Dispersive X-ray (EDX) analysis. The optical energy bandgap of the material, determined to be 2.81 eV, was ascertained through UV-visible absorption spectroscopy. Furthermore, the refractive index was calculated using both the Moss and the Herve and Vandamme methods. The study also delved into the electrical characteristics of the material, such as permittivity (εr), loss tangent (tanδ), and conductivity (σ). These properties were analyzed in relation to changes in frequency and temperature, employing particular formulas and parameters for a comprehensive understanding.
Research on Embedded 3D Simulation System for Collaborative Robots
Authors: Gao Shan , Geng Hua , Ge YaQiong , Zhang WenBin
Published: February 2024

In this article designing an embedded simulation system for heavy collaborative robots. From the perspective of control system autonomy, controllability, and economy, the selection of ARM SOC for the embedded computer hardware, LCD driver for the upper computer, Linux operating system, and OpenCasCade for the 3D geometry engine were completed. The localization rate of the industrial robot control system was improved while ensuring performance requirements. Establish a kinematic mathematical model of the robot based on the DH parameter method, and obtain the kinematic equation of the robot's end effector. Simultaneously building an ARM Linux environment that can run simulation systems, using the 3D geometry engine OpenCasCade to load the robot standard STEP model file, using QtCreator to simulate and model the robot, and conducting instance simulations. By analyzing the motion of the robot through simulation results, the correctness of the kinematic algorithm was verified, which meets the expected design goals and provides a reliable basis for the research of collaborative robot trajectory planning and control。
Prediction of Heart Failure in Type 2 Diabetes Mellitus Subjects Using Machine Learning: A Cross-Sectional Study
Authors: Alake Alake Oluwapelumi A. , Oluboyo Oluboyo Adeola O , Odewusi Odewusi Odeyinka O.
Published: February 2024

The concomitance of Type 2 Diabetes Mellitus (T2DM) and heart failure has made scientists investigate ways the onset of heart failure in T2DM can be predicted. Machine learning techniques have been shown to help with the prediction of heart disease and several model algorithms have been affirmed as good. This study aimed at predicting heart failure in T2DM subjects using machine learning techniques. A total of 123 blood samples from 59 healthy subjects without T2DM (controls) and 63 T2DM subjects (tests) were analyzed for biochemical parameters [troponin (TnI), electrolytes, Lactate dehydrogenase (LDH), Aspartate aminotransferase (AST), Alanine transaminase (ALT), AST/ALT ratio, Creatinine phosphokinase (CK-MB), Fasting Blood Sugar (FBS), Cholesterol, Triglyceride, B-Natriuretic peptide (BNP)] using standard procedures. Demographic data and biochemical results were all subjected to machine learning algorithms. The results of ML showed that the Random Forest algorithm is the best model for heart failure prediction with 87% accuracy. SHAP value (impact on model output) among all possible combinations identified glucose (FBG), BNP, Systolic and diastolic blood pressure, and waist circumference as important features in the prediction of heart failure in T2DM. The permutation importance score of the features studied showed systolic BP, BNP, MUAC and troponin I in this order to have the highest positive importance to the prediction of heart failure in T2DM. Height, weight, and waist circumference have small negative importance values meaning they slightly decrease model performance. The study concluded that CK-MB, BNP, and troponin I alone may not be early indicators of heart failure in T2DM subjects. However, subjecting them to ML and combining them with the key features identified would make prediction better.
Delivery rate alters the effects of tire wear particles on soil microbial activities
Authors: Zhu Yanjie , Kim Shin Woong , Li Huiying , Rillig Matthias C.
Published: February 2024

Background
Tire wear particles (TWPs) produced by the abrasion between tires and road surfaces have been recognized as an emerging threat to soil health globally in recent years. They can be transported from the road surface to adjacent soil at different delivery rates, with precipitation a main driver underpinning this movement. However, studies typically assume an abrupt exposure of TWPs in their experimental design. In this study, we investigated the impacts of abrupt and gradual delivery of TWPs on soil physicochemical properties and microbial activities. We used two different delivery rates of TWPs (abrupt and gradual) and devised two experimental phases, namely the TWPs-delivery period (phase 1) and the end-of-delivery period (phase 2).
Results
We found that the gradual TWPs delivery treatments negatively influenced the activity of carbon cycle-related enzymes (β-glucosidase and β-D-1,4-cellobiosidase). Furthermore, the abrupt treatment highly increased the effects on nitrogen cycle-related enzyme activity (β-1,4-N-acetyl-glucosaminidase). In phase 2 (end-of-delivery period), each enzyme activity was changed to a similar level as the control group, but these changes were influenced by the prior delivery rates.
Conclusion
Abruptly and gradually delivered TWPs induce different responses to soil microbial activities. Our findings imply that the delivery rate of TWPs could be another key factor changing the effects of TWPs, further enhancing our understanding of the ecological impacts of TWPs.
Graphical abstract