bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial intelligence for improving Nitrogen Dioxide forecasting of Abu Dhabi environment agency ground-based stations
Authors: AlShehhi Aamna , Welsch Roy 
Published: June 2023

AbstractNitrogen Dioxide (NO$$_{2}$$

2

) is a common air pollutant associated with several adverse health problems such as pediatric asthma, cardiovascular mortality,and respiratory mortality. Due to the urgent society’s need to reduce pollutant concentration, several scientific efforts have been allocated to understand pollutant patterns and predict pollutants’ future concentrations using machine learning and deep learning techniques. The latter techniques have recently gained much attention due it’s capability to tackle complex and challenging problems in computer vision, natural language processing, etc. In the NO$$_{2}$$

2

context, there is still a research gap in adopting those advanced methods to predict the concentration of pollutants. This study fills in the gap by comparing the performance of several state-of-the-art artificial intelligence models that haven’t been adopted in this context yet. The models were trained using time series cross-validation on a rolling base and tested across different periods using NO$$_{2}$$

2

data from 20 monitoring ground-based stations collected by Environment Agency- Abu Dhabi, United Arab Emirates. Using the seasonal Mann-Kendall trend test and Sen’s slope estimator, we further explored and investigated the pollutants trends across the different stations. This study is the first comprehensive study that reported the temporal characteristic of NO$$_{2}$$

2

across seven environmental assessment points and compared the performance of the state-of-the-art deep learning models for predicting the pollutants’ future concentration. Our results reveal a difference in the pollutants concentrations level due to the geographic location of the different stations, with a statistically significant decrease in the NO$$_{2}$$

2

annual trend for the majority of the stations. Overall, NO$$_{2}$$

2

concentrations exhibit a similar daily and weekly pattern across the different stations, with an increase in the pollutants level during the early morning and the first working day. Comparing the state-of-the-art model performance transformer model demonstrate the superiority of ( MAE:0.04 (± 0.04),MSE:0.06 (± 0.04), RMSE:0.001 (± 0.01), R$$^{2}$$

2

: 0.98 (± 0.05)), compared with LSTM (MAE:0.26 (± 0.19), MSE:0.31 (± 0.21), RMSE:0.14 (± 0.17), R$$^{2}$$

2

: 0.56 (± 0.33)), InceptionTime (MAE: 0.19 (± 0.18), MSE: 0.22 (± 0.18), RMSE:0.08 (± 0.13), R$$^{2}$$

2

:0.38 (± 1.35) ), ResNet (MAE:0.24 (± 0.16), MSE:0.28 (± 0.16), RMSE:0.11 (± 0.12), R$$^{2}$$

2

:0.35 (± 1.19) ), XceptionTime (MAE:0.7 (± 0.55), MSE:0.79 (± 0.54), RMSE:0.91 (± 1.06), R$$^{2}$$

2

: $$-$$
-
4.83 (± 9.38) ), and MiniRocket (MAE:0.21 (± 0.07), MSE:0.26 (± 0.08), RMSE:0.07 (± 0.04), R$$^{2}$$

2

: 0.65 (± 0.28) ) to tackle this challenge. The transformer model is a powerful model for improving the accurate forecast of the NO$$_{2}$$

2

levels and could strengthen the current monitoring system to control and manage the air quality in the region.
Myrtus communis L.: essential oil chemical composition, total phenols and flavonoids contents, antimicrobial, antioxidant, anticancer, and α-amylase inhibitory activity
Authors: Al-Maharik Nawaf , Jaradat Nidal , Al-Hajj Nisreen , Jaber Summayah 
Published: June 2023

Abstract
Background
Myrtuscommunis L. leaves, due to their tonic and antiseptic properties, have been used as folk medicine in many communities to treat a variety of conditions such as inflammation, peptic ulcers, diarrhea, leucorrhoea, headaches, excessive perspiration, and skin diseases. In this study, we examined the chemical makeup and biological properties of M.communis essential oils (EOs) from two locations in Palestine, including Jericho, the world's deepest site and Jenin. The plant's methanol and ethyl acetate extracts' biological efficacy were also assessed.

Results
The GC–MS analysis revealed that the EO of M.communis leaves from Jenin included 39 components, the majority were 1,8-cineole (31.98%), linalool (21.94%), linalool acetate (11.42%), α-pinene (10.22%), and myrtenol (6.87%). While 33 compounds, were discovered in M.communis EO from Jericho, with cis-4-thujanol (27.37%), 1,8-cineole (24.32%), myrtenol (12.97%), and myrtenal (12.46%) being the main constituents. The EO, ethyl acetate, and methanol extracts were tested (in vitro) for antibacterial, anticancer, antioxidant, and α-amylase inhibitory properties. The EO from Jericho demonstrated greater antibacterial efficacy against Escherichiacoli, Proteusvulgaris,Klebsiellapneumoniae, Staphylococcusaureus, and, methicillin-resistant Staphylococcusaureus (MRSA) with MIC values of 0.27, 0.135, 0.135, 0.27, and 0.135 mg/mL, respectively. MRSA, S.aureus and C.albicans were all susceptible to the antimicrobial efficiency of methanol and ethyl acetate extracts (MIC = 0.097–0.195, 0.097–0.195, and 0.049 mg/mL, respectively). Methanol and ethyl acetate extracts, in contrast to EOs, showed high DPPH activity, with IC50 values ranging from 3.60 ± 0.35 to 25.70 ± 0.48 µg/mL. Both oils showed moderate cytotoxic activity against HeLa, MCF7, 3T3, and LX-2 cell lines, with IC50 values ranging from 202.02 ± 2.27 to 592.40 ± 2.55 µg/mL for Jenin and 199.80 ± 3.41 to 914.54 ± 3.05 µg/mL for EO from Jericho. Furthermore, EO and methanol extracts from Jenin inhibited α-amylase with IC50 values of 950.48 ± 2.54 and 795.43 ± 1.88 µg/mL, respectively.

Conclusions
Our findings indicate that M.communis extracts and EOs contain a vast array of pharmacologically active compounds with potent antioxidant, antibacterial, and antifungal activities that can be exploited to develop new types of natural pharmaceuticals and warrant further in vivo investigation for their therapeutic potential.

Graphical Abstract
Spatiotemporal and meteorological relationships in dengue transmission in the Dominican Republic, 2015–2019
Authors: Robert Michael A. , Rodrigues Helena Sofia , Herrera Demian , de Mata Donado Campos Juan , Morilla Fernando , Del Águila Mejía Javier , Guardado María Elena , Skewes Ronald , Colomé-Hidalgo Manuel 
Published: June 2023

AbstractDengue has broadened its global distribution substantially in the past two decades, and many endemic areas are experiencing increases in incidence. The Dominican Republic recently experienced its two largest outbreaks to date with 16,836 reported cases in 2015 and 20,123 reported cases in 2019. With continued increases in dengue transmission, developing tools to better prepare healthcare systems and mosquito control agencies is of critical importance. Before such tools can be developed, however, we must first better understand potential drivers of dengue transmission. To that end, we focus in this paper on determining relationships between climate variables and dengue transmission with an emphasis on eight provinces and the capital city of the Dominican Republic in the period 2015–2019. We present summary statistics for dengue cases, temperature, precipitation, and relative humidity in this period, and we conduct an analysis of correlated lags between climate variables and dengue cases as well as correlated lags among dengue cases in each of the nine locations. We find that the southwestern province of Barahona had the largest dengue incidence in both 2015 and 2019. Among all climate variables considered, lags between relative humidity variables and dengue cases were the most frequently correlated. We found that most locations had significant correlations with cases in other locations at lags of zero weeks. These results can be used to improve predictive models of dengue transmission in the country.
Analysis and prediction of pipeline corrosion defects based on data analytics of in-line inspection
Authors: Cui Bingyan , Wang Hao 
Published: June 2023

AbstractIn-line inspection (ILI) is important to pipeline integrity management since it can detect pipeline defects and identify potential failure locations through periodical examinations. However, effectively evaluating defects based on ILI data is challenging. Measurements of ILI are easily influenced by instrument performance and maintenance activities, leading to unmatched and imbalanced data. Poor ILI data make it difficult to establish defect growth models based on multiple inspections. This study conducted comprehensive analysis of ILI data for evaluating corrosion defects of a steel pipeline. First, statistical analysis was performed on raw data to visualize distributions of corrosion depths and number of corrosions. Second, hierarchical clustering method was used to classify corrosion severity levels based on features of corrosion depth and estimated repair factor. The interaction effect between adjacent corrosions was considered. Machine learning methods, including k-nearest neighbor, support vector machine, random forest, and light gradient boosting machine were used to explore the relationship between the location parameters of adjacent corrosions and severity levels. Then, maximum corrosion depths and corrosion density were filtered from raw ILI data of multiple inspections, which were critical for pipeline failure prediction. Finally, distribution parameters were fitted to establish stochastic growth models on maximum corrosion depth and corrosion number density. This study presents data analytics based approach to obtain valid information from ILI data in practice.
A feasibility study on time-lapse transient electromagnetics for monitoring groundwater dynamics
Authors: Zamora-Luria Juan Carlos , McLachlan Paul , Maurya Pradip Kumar , Liu Lichao , Grombacher Denys , Christiansen Anders Vest 
Published: June 2023

Time-lapse geophysical studies have been used as noninvasive tools to study subsurface processes. However, compared to direct current resistivity methods, the transient electromagnetic (TEM) method has not been explored in much detail for time-lapse investigations. Here, we introduce the use of a monitoring TEM (mTEM) system and methodology for long-term groundwater monitoring purposes. The system can run measurements automatically and the modeling approach uses a time-constrained inversion (TCI) scheme based on an existing laterally constrained inversion scheme. Instead of lateral constraints that traditionally ensure lateral coherency between measurements, temporal constraints are used to control the temporal coherency between measurements. Synthetic analysis demonstrates that very tight time constraints on resistivities and a time constraint on the depth to the water table fixed at a fraction of the expected annual water table variation is needed to track water table changes at the decimeter level. Furthermore, the synthetic analysis indicates that the mTEM method can track annual variations in the water table with amplitudes as low as 0.6 m with a mean absolute error of 0.2 at depths between 16 m and 30 m. A field example consisting of 233 1D TEM measurements acquired over 10 months using the mTEM instrument supports the synthetic results. The estimated water table depth from the TCI scheme reproduces the variation in the water table accurately, as confirmed by measurements from a water level data logger in a nearby well. The differences between the results from the TEM monitoring system and the diver measurements are in the range of ±0.1 m with an average absolute difference of 0.05 m. This study demonstrates the potential to monitor changes in the groundwater level noninvasively.
Racial Disparities in the Ascertainment of Cancer Recurrence in Electronic Health Records
Authors: Khor Sara , Heagerty Patrick J. , Basu Anirban , Haupt Eric C. , Lyons Lindsay Joe L. , Hahn Erin E. , Bansal Aasthaa 
Published: June 2023

PURPOSE There is growing interest in using computable phenotypes or proxies to identify important clinical outcomes, such as cancer recurrence, in rich electronic health records data. However, the race/ethnicity-specific accuracies of these proxies remain unclear. We examined whether the accuracy of a proxy for colorectal cancer (CRC) recurrence differed by race/ethnicity and the possible mechanisms that drove the differences. METHODS Using data from a large integrated health care system, we identified a stratified random sample of 282 Black/African American (AA), Hispanic, and non-Hispanic White (NHW) patients with CRC who received primary treatment. Patient 5-year recurrence status was estimated using a utilization-based proxy and evaluated against the true recurrence status obtained using detailed chart review and by race/ethnicity. We used covariate-adjusted probit regression models to estimate the associations between race/ethnicity and misclassification. RESULTS The recurrence proxy had excellent overall accuracy (positive predictive value [PPV] 89.4%; negative predictive value 96.5%; mean difference in timing 1.96 months); however, accuracy varied by race/ethnicity. Compared with NHW patients, PPV was 14.9% lower (95% CI, 2.53 to 28.6) among Hispanic patients and 4.3% lower (95% CI, −4.8 to 14.8) among Black/AA patients. The proxy disproportionately inflated the 5-year recurrence incidence for Hispanic patients by 10.6% (95% CI, 4.2 to 18.2). Compared with NHW patients, proxy recurrences for Hispanic patients were almost three times as likely to have been misclassified as positive (adjusted risk ratio 2.91 [95% CI, 1.21 to 8.31]). Higher false positives among racial/ethnic minorities may be related to higher prevalence of noncancerous lung-related problems and substantial delays in primary treatment because of insufficient patient-provider communication and abnormal treatment patterns. CONCLUSION Using a proxy with worse accuracy among racial/ethnic minority patients to estimate population health may misdirect resources and support erroneous conclusions around treatment benefit for these patients.
Isotropic Ge3Sb2Te6 metasurfaces for mid-infrared wavefront steering
Authors: Zhang Yuyang , Li Changqing , Song Zhengyong 
Published: June 2023

Abstract
Due to unprecedented electromagnetic properties, germanium antimony telluride (GST) plays a crucial role in the field of electromagnetic wavefront control. With the purpose of mid-infrared wavefront reconfiguration, eight

meta-atoms are proposed. Meta-atoms appear in different phase states as

state is switched. As crystalline

is involved, eight meta-atoms reach full phase coverage with phase gradient of 45°. As

is switched to amorphous state, phase difference between adjacent meta-atoms no longer varies uniformly by 45°, thus losing original properties. Based on eight meta-atoms, four metasurfaces are presented to verify characteristics, which are two metalenses and two orbital angular momentum (OAM) generators. As crystalline

is switched to amorphous

, dynamical manipulation between focusing and defocusing is realized. Besides, OAM mode of vortex beam is reconstructed from

or 2 to

. Our designs could find potential applications in focusing, switching, and encryption.
Muon Spin Rotation (μSR) for Characterizing Radical Addition to C=S in Xanthene-9-thione and Thioxanthene-9-thione
Authors: Ito Shigekazu , Akama Hikaru , Kojima Kenji M , McKenzie Iain , Kuwahata Kazuaki , Tachikawa Masanori 
Published: June 2023

Abstract
Muonium (μ+e−) can be produced by capture of an electron by a spin-polarized muon (μ+) and has been utilized as a light isotope of hydrogen. In this paper, we demonstrate muon spin rotation (μSR) experiments and preliminary computational analyses of the regioselective muonium addition to xanthene-9-thione and thioxanthene-9-thione providing the C-centered radicals. The transverse-field muon spin rotation (TF-μSR) experiments of the cyclic thioketones revealed considerable increase of muon hyperfine coupling constants (muon hfc, Aμ) compared with the muoniated thiobenzophenone, indicating crucial roles of the bridging chalcogen atom promoting the overlap between the S–Mu bond orbital and the radical p orbital.
Acute radiation syndrome
Authors: Zuziak Patrycja , Bielaska Agnieszka 
Published: June 2023

Over the last decades, along with progress and development of using ionizing radiation, including the fields of power engineering or nuclear weapons, it was possible to observe and describe negative effects of the radiation on human body. The phenomenon referred to as acute radiation syndrome describes the effects of radiation on living cells, depending on exposure time and absorbed dose, which affects the functioning of entire organism after the exposure. The following work describes how ionizing radiation causes changes at the cellular and tissue level, both directly and indirectly, taking into account the variables affecting final effects of exposure. Consecutive phases of acute radiation syndrome were distinguished, and the focus was also on individual groups of disorders resulting from exposure, which may overlap and coexist, i.e. hematopoietic syndrome, gastrointestinal syndrome and neurovascular syndrome, as well as developing multi-organ failure in some of the cases, leading to the patient's death. Exposure to ionizing radiation can result in diversified, variably intensified and spread over time symptoms from many organ systems. Depending on the characteristics of the exposure, its effects will differ, and thus the prognosis for the patient.
Digesting FOREXS: Information Transmission Across Asset Classes and Return Predictability
Authors: Bae Joon Woo , Da Zhi , Zurita Virgilio 
Published: June 2023

We provide novel evidence that equity investors react to currency shocks with a delay. Using the cross-section of currency returns and the relative presence of U.S. firms in foreign economies, we compute a foreign operations-related exchange shock (FOREXS) measure. We find FOREXS to predict firms’ future cash flows and stock returns, driving much of the previously documented underreaction to foreign information. An FOREXS-based long-short strategy yields a 6.74% annualized abnormal return. FOREXS predictive power comes from firms’ incomplete hedging and investors’ limited attention, highlighting the challenges involved when processing information from a different asset class. This paper was accepted by David Sraer, finance. Funding: Z. Da acknowledges financial support from the Beijing Outstanding Young Scientist Program [Grant BJJWZYJH01201910034034] and the 111 Project [Grant B20094]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4778 .
Formation and Routing of Worker Teams for Airport Ground Handling Operations: A Branch-and-Price-and-Check Approach
Authors: Dall’Olio Giacomo , Kolisch Rainer 
Published: June 2023

We address workforce optimization for ground handling operations at the airport, focusing on baggage loading and unloading. Teams of skilled workers have to be formed and routed across the apron to unload the baggage from the aircraft after a landing and to load it before takeoff. Such tasks must be performed within time windows and require a team of workers with different skill levels. The goal is to find a feasible plan that minimizes the sum of the tasks completion times. We formalize a variation of the workforce scheduling and routing problem, integrating team formation, hierarchical skills with downgrading, multiple trips, and different execution modes. We propose a solution approach based on branch-and-price-and-check and test it on real-world instances from a major European hub airport. We propose a model based on the Dantzig–Wolfe decomposition. In the pricing problem, we generate tours of teams as shortest paths with constrained resources in a network. In the master problem, we select an optimal set of tours that do not exceed the workforce availability. Our experiments show that the proposed algorithm can produce optimal solutions for small- and medium-sized instances and good or optimal solutions for large instances. The results also show that our approach outperforms the current airport dispatching policy. Funding: G. Dall’Olio was funded by the Deutsche Forschungsgemeinschaft [Grant Advanced Optimization in a Networked Economy Graduiertenkolleg 2201, Project 277991500]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0110 .
Simulating movements of daily living in robot-assisted total hip arthroplasty with 3D modelling
Authors: Tung Wei S. , Donnelley Claire , Pour Aidin E. , Tommasini Steven , Wiznia Daniel 
Published: June 2023

AimsComputer-assisted 3D preoperative planning software has the potential to improve postoperative stability in total hip arthroplasty (THA). Commonly, preoperative protocols simulate two functional positions (standing and relaxed sitting) but do not consider other common positions that may increase postoperative impingement and possible dislocation. This study investigates the feasibility of simulating commonly encountered positions, and positions with an increased risk of impingement, to lower postoperative impingement risk in a CT-based 3D model.MethodsA robotic arm-assisted arthroplasty planning platform was used to investigate 11 patient positions. Data from 43 primary THAs were used for simulation. Sacral slope was retrieved from patient preoperative imaging, while angles of hip flexion/extension, hip external/internal rotation, and hip abduction/adduction for tested positions were derived from literature or estimated with a biomechanical model. The hip was placed in the described positions, and if impingement was detected by the software, inspection of the impingement type was performed.ResultsIn flexion, an overall impingement rate of 2.3% was detected for flexed-seated, squatting, forward-bending, and criss-cross-sitting positions, and 4.7% for the ankle-over-knee position. In extension, most hips (60.5%) were found to impinge at or prior to 50° of external rotation (pivoting). Many of these impingement events were due to a prominent ischium. The mean maximum external rotation prior to impingement was 45.9° (15° to 80°) and 57.9° (20° to 90°) prior to prosthetic impingement. No impingement was found in standing, sitting, crossing ankles, seiza, and downward dog.ConclusionThis study demonstrated that positions of daily living tested in a CT-based 3D model show high rates of impingement. Simulating additional positions through 3D modelling is a low-cost method of potentially improving outcomes without compromising patient safety. By incorporating CT-based 3D modelling of positions of daily living into routine preoperative protocols for THA, there is the potential to lower the risk of postoperative impingement events.Cite this article: Bone Jt Open 2023;4(6):416–423.
The Undercover Research Group and the Spycops scandal: research in the defence of the right to protest and transparency
Authors: Brian Christopher , Lubbers Eveline 
Published: June 2023

Between 1968 and 2010 more than one thousand groups and many more individuals on the left of the political spectrum were targeted by intrusive police surveillance.
This intervention gives an overview of what has become known as the Spycops scandal and the active role of the grassroot movements that were spied on, while focusing on the authors’ own organisation, the Undercover Research Group.
It explores how a critical approach to the Undercover Policing Inquiry had been productive, while conceding that misgivings about engagement are understandable and valid as well.
This paper also considers how the impact of this mode of policing are still being felt today and discusses whether the current hostile environment for protesters makes a reoccurrence of these abuses more likely.