bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Practical Framework for Oil and Gas Operators to Estimate Methane Emission Duration Using Operational Data
Authors: Higgins Shaun , Hecobian Arsineh , Baasandorj Munkhbayar , Pacsi Adam P. 
Published: January 2024

Summary
Methane management is a key greenhouse gas (GHG) reduction focus within the oil and gas industry. While there are a variety of techniques for methane detection and measurement, aircraft-mounted sensors have become popular for both academic studies and operators in onshore regions in North America due to their ability to screen many sites in a relatively short amount of time. Many traditional leak detection and repair (LDAR) techniques, like optical gas imaging (OGI), and emerging approaches, such as aircraft-based or satellite-based screenings, are periodic, which means that they can provide information about the presence of emissions and approximate rates during the observation period. Scaling periodic observations to annual emission estimates needed for regulatory and corporate reporting requires information on emission duration, which is not generally provided by the same screening techniques. In the literature to date, there have been several statistical approaches proposed for the annualization of basin-level methane observations, but these techniques may struggle to downscale to individual operators, across which methane emission intensities are expected to vary. In this paper, we propose a novel, conceptual framework for using other sources of data, such as records from operator inspections and parametric monitoring, to help define the duration of detected methane emissions. Such information may prove to be a useful input to measurement-informed methane emission protocols that are under development by multistakeholder groups, like GTI Energy Veritas and federal agencies in the United States.
5-Aminolevulinic Acid Tumor Paint and Photodynamic Therapy for Chordoma: An In Vitro Study
Authors: Kenan Shachar , Nixon Ryan , Liang Haixiang , Goodman Howard J. , Grande Daniel A. , Levin Adam S. 
Published: January 2024

Abstract
Background:
Wide resections of chordoma tumors are challenging for many reasons, primarily due to a lack of intraoperative visualization, leading to unacceptably high recurrence rates. Known techniques using five-aminolevulinic acid (5-ALA) for tumor paint and photodynamic therapy (PDT) may improve outcomes but have not been well described for chordomas. This study aimed to analyze chordoma cell response to 5-ALA tumor paint and PDT in vitro.

Methods:
Tumor paint: Human chordoma cells (MUG-Chor1) were cocultured with green fluorescence protein (GFP) rat adipose-derived stromal cells (ADS) with subsequent observation after 5-ALA exposure, visualized using filters to show GFP cells in green and 5-ALA positive cells in red color.
PDT: MUG-Chor1 and ADS cells were exposed separately to 5-ALA followed by PDT treatment using 405-nm excitation and emission at 603-738-nm. Time-lapse images of live cells were captured every second for 15 minutes and then visualized sequentially at 50× speed.

Results:
The tumor paint arm of the study successfully demonstrated selective red chordoma fluorescence, a finding which may facilitate visualization of a malignancy juxtaposed to surrounding benign healthy tissue. The second arm of the study, PDT, demonstrated selective chordoma cellular death, clearly evidenced by swelling and vesicle formation in contrast to the ADS control.

Conclusion:
The results of these experiments demonstrate the effective in vitro application of 5-ALA tumor paint and PDT on chordoma cells, documented visually using time-lapse photography. 5-ALA, with its double-edged applications of selective tumor identification and kill, may lead to transformative change in the management of soft tissue sarcomas.
A previously undescribed scene-selective site is the key to encoding ego-motion in naturalistic environments
Authors: Kennedy Bryan , Malladi Sarala N. , Tootell Roger BH , Nasr Shahin 
Published: January 2024

Abstract

Current models of scene processing in the human brain include three scene-selective areas: the Parahippocampal Place Area (or the temporal place areas; PPA/TPA), the restrosplenial cortex (or the medial place area; RSC/MPA) and the transverse occipital sulcus (or the occipital place area; TOS/OPA). Here, we challenged this model by showing that at least one other scene-selective site can also be detected within the human posterior intraparietal gyrus. Despite the smaller size of this site compared to the other scene-selective areas, the posterior intraparietal gyrus scene-selective (PIGS) site was detected consistently in a large pool of subjects (n=59; 33 females). The reproducibility of this finding was tested based on multiple criteria, including comparing the results across sessions, utilizing different scanners (3T and 7T) and stimulus sets. Furthermore, we found that this site (but not the other three scene-selective areas) is significantly sensitive to ego-motion in scenes, thus distinguishing the role of PIGS in scene perception relative to other scene-selective areas. These results highlight the importance of including finer scale scene-selective sites in models of scene processing – a crucial step toward a more comprehensive understanding of how scenes are encoded under dynamic conditions.
Significance of Healthcare Analysis Using Word Embedding With Machine learning Classifiers
Authors: Roy Somen Kumar , Pillai Jyothi , Thomas Ani 
Published: January 2024

Abstract

The forecasting of health news is becoming the main issue to divide healthcare news into different classes based on user comments. Moreover, predicting class content is significantly important in influencing news forecast reports. In this paper, the news data from the MIND dataset considered classes lifestyle and health with user comments, in the preprocessing stage tokenization, stop word removal, stemming, lemmatization etc. are performed. After the preprocessing step obtained words need to be converted into numerical vectors and these vectors along with their weighted values are determined for Modeling, in this way applied to some techniques like Word embedding, feature selection, SMOTE (synthetic minority class over-sampling technique) and various ML (machine learning) classifiers To find the impact of used techniques for the given input data and the performance of all used techniques is obtained by some descriptive statistics analysis and Rank test. Finally, the comparative analysis is shown by the performance of accuracy and F-measure parameters for each technique. Experiments show that the LOGR (logistic regression) and a variant of SVM outperform all other classifiers and it is seen that in this work GLOVE variant is a better embedding technique where CCRA (cross correlation analysis) and SMOTE are better feature selection and class imbalance techniques and their combined effects helps to achieve significant improvement for the models to predict the classes priority based on news comments by users.
WITHDRAWN: Numerical Study on the Performance Evaluation and Thermal Management of Automotive Exhaust Thermoelectric Generator using Pin fins
Authors: Veer Chander , Kansara Keyur , Singh Shobhana 
Published: January 2024

Abstract
The utilization of thermoelectric power generators presents a viable prospect for the recuperation of waste heat that results from exhaust gases within the automotive sector. The optimal performance of thermoelectric modules in waste heat recovery applications is heavily dependent on the design of the heat exchanger. The current study employs numerical methods to examine the efficacy of pin-fin configurations on the hot-side heat exchanger surface in enhancing heat transfer and thereby improving the conversion efficiency of TEG. Specifically, the study explores the impact of inline, staggered, and progressive arrangements of pin-fins in the direction of the exhaust stream. The heat exchanger is subjected to variations in fin thickness ranging from 10 mm to 18 mm to improve heat transfer in each configuration. The study conducts simulations on every fin configuration, utilizing three distinct inlet velocities (4 m/s, 6 m/s, and 8 m/s) and five different inlet temperatures (423 K, 473 K, 523 K, 573 K, and 623 K). The assessment of the heat exchanger’s performance is conducted by means of the thermal-hydraulic performance coefficient (THPC) and the temperature uniformity index. Meanwhile, the evaluation of the TEG device’s performance is carried out by estimating its rated power output and the conversion efficiency of TEG. According to the findings, the staggered fin arrangement exhibits the highest Thermal Hydraulic Performance Coefficient (THPC) and power generation capability, while the progressive and inline fin configurations follow in descending order. The utilization of fins with a thickness of 18 mm in a staggered arrangement yields a peak rated power output of 53.42 W. The implementation of pin fins in a staggered configuration within the heat exchanger amplifies the heat transfer from the exhaust gas to the thermoelectric module. Consequently, there is an increase in the output power with respect to the given temperature difference.
Evaluating adolescent outcomes and staff member injuries following treatment on a general psychiatric inpatient unit
Authors: Romani Patrick W. , Anjom Ava , Anderson Tyler , Ariefdjohan Merlin 
Published: January 2024

Abstract

Brief psychiatric hospitalization represents an intervention used to manage acute crisis behaviors (e.g., out-of-control behavior; suicidal ideation) exhibited by children and adolescents. To date, few studies have presented their clinical model of care in addition to key outcome metrics, such as patient outcome and staff injury. Studies sharing this type of information could provide descriptions of desperately needed clinical models to ensure that standards of care for both patients and staff are met on psychiatric inpatient units. The purpose of the current study was to describe one unit’s clinical model emphasizing group therapy grounded in the principles of dialectical behavior therapy within a brief psychiatric inpatient admission (mean length of stay = 8 days). We provide outcome data on patient symptoms of depression, anxiety, and anger upon discharge from the hospital, patient satisfaction with the hospitalization, and staff member safety on the unit. This programming produced statistically significant changes in adolescent symptoms of depression, anxiety, and anger at the time of discharge from their brief psychiatric hospitalization. Patients also reported a high level of satisfaction with the services received. While these outcomes were promising, we recorded a high rate of staff member injury while delivering care. We were unable to identify a patient profile that contributed to staff member injury but did identify relations between staffing ratios, time of day, and staff member injury. We hope to share this information in an attempt to provide additional evidence regarding the effectiveness of these brief inpatient programs as well as to draw awareness to variables that may influence staff member experience on these units.
How safe is safely managed on-site sanitation? What we need to know beyond global monitoring
Authors: Mills Freya , Foster Tim , Kome Antoinette , Munankami Rajeev , Halcrow Gabrielle , Ndungu Antony , Evans Barbara , Willetts Juliet 
Published: January 2024

Abstract

Halfway through the Sustainable Development Goal (SDG) period, there has been little research on the criteria for monitoring safely managed sanitation under SDG target 6.2. For reporting against SDGs, global indicators are necessarily limited and exclude many safety aspects from a public and environmental health perspective. Primary survey data from 31,784 households in seven countries in Asia and Africa were analysed, comparing estimates of safely managed on-site sanitation based on global indicators with five complementary indicators of safety: animal access to excreta, flooding and overflow, groundwater contamination, emptying frequency, and the safety of emptying. Application of additional criteria reduced the population with safely managed sanitation by 0.4-38% for specific indicators, with the largest impact due to the risk of groundwater contamination, animal access, and containments overdue for emptying. Combining these indicators across the service chain, excluding transport and treatment, found three-quarters of on-site systems currently assessed as safely managed with global indicators were considered unsafe based on complementary indicators. A more comprehensive assessment of safety of on-site sanitation can be achieved through these indicators, which could be integrated into national monitoring systems and used to inform sanitation investments that address local health related risks.
Ice-assisted soft-landing deposition for van der Waals integration
Authors: Qiu Min , Sun Xinyu , Jin BinBin , Lu Yihan , Zhao Ding 
Published: January 2024

Abstract
Van der Waals integration enables the creation of electronic and optoelectronic devices with unprecedented performance and novel functionalities beyond the existing material limitations. However, it is typically realized using a physical pick-up-and-place process to minimize interfacial damages and is hardly integrated into conventional lithography and metallization procedures. Here we demonstrate a simple and ultra-clean in situ transfer strategy for van der Waals integration, in which a thin film of amorphous water ice acts as a buffer layer to shield against the bombardment of energetic clusters during metallization. After ice sublimation, the deposited metal film can be gently and in situ placed onto underlying substrates, e.g., 2D semiconductors, to form an atomically clean and damage-free metal-semiconductor interface. We use this strategy to demonstrate the non-destructive fabrication of high-quality contacts on monolayer MoS2, which is extremely beneficial to produce a high-performance 2D field-effect transistor with an ultra-high on/off ratio of 1010, mobility of 80 (cm2 V-1s-1), and also with reduced Fermi level pinning effect. Benefiting from the chemical residue-free and gentle fabrication approach, this strategy could also widen the existing range of materials for vdW integration. Our method can be easily integrated with mature semiconductor manufacturing technology and may become a generic strategy for fabricating van der Waals contacted devices.
Graphitic carbon nitride supported Fe single-atom nanozymes synergize with nitrate reductase for photobiocatalytic nitrate conversion
Authors: An Xiaoqiang , Bian Jiyong , Zhao Jing , Lan Xianen , Liao Yang , Liu Ruiping , Liang Minmin , Tang Junwang , Liu Huijuan , Qu Jiuhui 
Published: January 2024

Abstract
Nitrate reduction is of paramount importance for both the restoration of natural ecosystems and the sustainable development of chemical industries, but faces challenges in the rate-limiting step of nitrate-nitrite conversion and the poor product selectivity of the multielectron reactions. Herein, we demonstrate a nitrate-to-nitrite photosynthesis route catalyzed by a biotic-abiotic nanoarchitecture composed of carbon nitride (C3N4) supported Fe single-atom nanozymes combined with native nitrate reductases. Under visible light irradiation, the photobiocatalyst exhibits a state-of-the-art capability for nitrate conversion, with nearly 100% selectivity of nitrate and an unprecedented reaction kinetic constant that far exceeds those of all reported visible-light-driven photocatalysts. The strong binding affinity of nanozyme to the reaction substrate contributes to the 68.9- and 20.2-fold enhancement in the activity compared to artificial C3N4 photocatalyst and natural NarGHI biocatalyst, respectively, far exceeding the biological enzymes and reported enzyme-mimicking nanomaterials for nitrate conversion. Mechanistic studies at the atomic- and molecular levels reveal that Fe single atoms and cyano (-C ≡ N) groups on C3N4 mimic the heme bD and heme bP in the NarI subunit and construct a unique electron transfer chain between the biotic-abiotic interface under visible light irradiation, contributing to efficient and selective nitrate reduction to nitrite via photobiocatalysis. This work represents a promising biotic-abiotic platform to address the bottleneck problems of nitrate conversion, offering new opportunities for the sustainable removal of nitrogen from water and ammonia energy production with low energy consumption and carbon emission.
Static Aeroelastic Rolling of a Highly Flexible Wing - Pazy Wing with Aileron
Authors: de Melo Felipe Buarque Cordeiro , Bussamra Flavio L. S. , Verri Angelo A. 
Published: January 2024

Abstract

There is an increasing trend towards the use of higher aspect-ratio wings on commercial transport aircraft over the years. The well-known effect of slender wings on reducing fuel consumption are leading wing designs to higher aspect ratios and higher flexibility. There are many studies about the effects of geometric nonlinearities on aeroelastic behavior of high aspect-ratio, very flexible, wings. However, geometric nonlinearities may also significantly impact wings’ aeroelastic behavior under nonsymmetrical conditions, specially when ailerons are deflected. Within this context, this work presents a static Fluid-Structure Interaction approach to evaluate the rolling characteristics of very flexible wings. First a modified version of the very flexible Pazy Wing, from Aeroelastic Prediction Workshop (AEPW-3), is proposed, now equipped with ailerons. Then, this work proposes a new framework to consider the geometric nonlinearity in a fluid-structure interaction, it loosely couples Full Potential aerodynamic solver with Implicit Nonlinear structural solver. The presented method was applied considering both linear and nonlinear structural analyses, with multiple aileron deflection angles. The results show that considering or neglecting geometric nonlinearities leads to qualitatively divergent predictions.
Rightward brain structural asymmetry in young children with autism
Authors: Cao Miao , Geng Shujie , Dai Yuan , Rolls Edmund , Liu Yuqi , Zhang Yue , Deng Lin , Chen Zilin , Feng Jianfeng , Li Fei 
Published: January 2024

Abstract

To understand the neural mechanisms of autism spectrum disorder (ASD) and developmental delay/intellectual disability (DD/ID) that can be associated with ASD, it is important to include brain, behavioural and also genetic measures and to investigate individuals at an early age, but such research is still lacking. Here, using structural MRI of 1030 children under 8 years old, we employed developmental normative models to investigate the atypical development of gray matter volume (GMV) asymmetry in individuals with ASD without DD/ID, ASD with DD/ID, and individuals with only DD/ID, and their associations with behavioural and clinical measures and transcription profiles. By computing the individual deviations from typical controls, we found increased right- vs left laterality in ASD children in the inferior parietal cortex and precentral cortex, and also higher variability in temporal pole asymmetry. In addition, ASD with DD/ID children had some cortical regions (e.g. the isthmus cingulate) with leftward asymmetry; ASD without DD/ID children had some cortical regions (e.g. the parahippocampal gyrus) with higher variability in asymmetry; and children with DD/ID without ASD showed no significant differences in asymmetry. The GMV laterality of ASD without DD/ID children was associated with ASD symptoms, whereas the laterality of ASD with DD/ID children was associated with both ASD symptoms and verbal IQ. Last, the GMV laterality of all three groups was significantly associated with shared and unique gene expression profiles. Our findings provide evidence for rightward GMV asymmetry of some cortical regions in young children (1–7 years) in a large sample (1030 cases), show that these asymmetries are related to ASD symptoms, and identify genes that are significantly associated with these differences.
An Automatic Ametropia Examination based on EEG Signals
Authors: Zhou Huaixuan , Zhang Ruyi , Fan Chixuan , Ren Hongyi , Ma Qingkai , Han Yishi , Gong Jianyang 
Published: January 2024

Abstract
Regular ametropia examination of human eye can effectively prevent the aggravation of ametropia. However, the use of the traditional ametropia examination method is limited to complicated manual operations and necessary communication between doctors and patients. In this study, we proposed a novel ametropia examination method, which determine the degree of ametropia by automatically processing and analyzing the event-related potentials (ERP), one kind of evoked electroencephalogram (EEG) signal. Specifically, we studied the correlation between one’s ametropia degree and his ERP signal features, and established the ametropia classification model based on ERP for the first time. In order to stably induce ERP from subjects, we designed a compound visual stimulus paradigm, which integrated three types of stimulus pictures to provide non-single stimulus. Furthermore, to realize automatic signal processing, we devised the eye movement artifact removal algorithm based on standard deviation as the threshold, the ERP component location algorithm based on peak and valley, and feature extraction formulas. In the test experiment, the examination accuracy of the method for low, moderate, and high ametropia is 86.29%, 80.95% and 90.98% respectively. And the average time of ERP feature extraction is 0.012 seconds. When 1.5 standard deviation was set as the threshold, the method can effectively identify and eliminate eye movement artifacts, and retain effective EEG signals. Compared with the traditional ametropia examination method, a novel ametropia classification model based on ERP proposed in this study can realize automatic ametropia examination by oneself and is more suitable for daily family examination.
Pollutants Exceedances Modeling using Non-Homogeneous Poisson Processes: A Case Study for Medellín and Bogotá, 2018-2020
Authors: Montoya Karen Melissa Gómez , Sierra Biviana Marcela Suárez , Taimal Carlos A. 
Published: January 2024

Abstract
In this paper, we present an alternative method to model the exceedances of the Colombian and global environmental standards for three pollutants, PM2.5, PM10 y O3, for the cities Colombia of Bogota´ and Medell´ın during the period of 2018-2020. The aforementioned is done using a stochastic model denominated the Non-Homogeneous Poisson Process with estimation employing Bayesian com putational methods. Through the usage of this methodology, it is intended to fit models with a highly predictive component for the case of Colombia and to allow interpretability through the parameters. Said methodology will allow for decisions to be made in terms of public policies. The best found models will, in the end, be all those that take into consideration the presence of two change-points or instants of variation. The change-points are given by the behavior of the country’s climate, public policies to mitigate pollution, the mandatory quarantine because of COVID-19 and infrastructure projects.