bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical Performance Study of a Fecal Bacterial Signature Test for Colorectal Cancer Screening
Authors: Malagón Marta , Alwers Elizabeth , Oliver Lia , Ramió-Pujol Sara , Sánchez-Vizcaino Mireia , Amoedo Joan , de Cambra Salomé , Serra-Pagès Mariona , Castells Antoni , Aldeguer Xavier , Garcia-Gil Jesús , Brenner Hermann 
Published: January 2023

Abstract
Background.
The fecal immunochemical test (FIT) is the most widely used test for colorectal cancer (CRC) screening. RAID-CRC Screen is a new non-invasive test based on fecal bacterial markers, developed to complement FIT by increasing its specificity. The test was previously clinically evaluated in FIT-positive patients (> 20 µg of hemoglobin/g of feces, “FIT20”), in which it reduced the proportion of false positive results by 16.3% while maintaining most of FIT20’s sensitivity. The aim of this study was to compare the sensitivity and specificity of a CRC screening program using RAID-CRC Screen in addition to FIT20 as a triage test in a European screening population undergoing screening colonoscopy with a CRC screening program with FIT20 alone in the same cohort.
Results.
A cohort of 2481 subjects aged > 55 years from the German screening colonoscopy program was included. The colonoscopy findings were used as the gold standard in calculating the diagnostic capacity of the tests and included 15 CRC and 257 advanced neoplasia cases. RAID-CRC Screen added to FIT20 provided the same sensitivity as FIT20 alone (66.7%) in detecting CRC and a significantly higher specificity (97.0% vs. 96.1%, p < 0.0001). The positive predictive value was 11.9% when using RAID-CRC Screen and 9.5% with FIT20 alone, and the negative predictive value was 99.8% in the two scenarios. For advanced neoplasia detection, the use of RAID-CRC Screen yielded significantly lower sensitivity than with FIT20 alone (17.5% vs. 21.8%, p = 0.0009), and the overall specificity was significantly higher when using RAID-CRC Screen compared with FIT20 alone (98.2% vs. 97.8%, p = 0.0039).
Conclusions.
Our findings confirm the results obtained in previous clinical studies in a CRC screening setting, showing the potential of RAID-CRC Screen to increase the overall specificity of FIT-based screening.
Design and experiments with a single spiral fixed depth ditching and fertilizing machine
Authors: Zhan Caixue , Ding Wenqin , Han Yu , Jiang Qinghai , Zhao Ying , Song Zhiyu , Zhao Liang 
Published: January 2023

Abstract
Aiming at the problems of low fertilization efficiency, mostly single process operation and inconsistent fertilization depth of domestic tea garden fertilizing machine, a single spiral fixed depth ditching and fertilizing machine was designed. The machine can complete the integrated operation of ditching, fertilization and covering soil at one time through the operation mode of single spiral ditching and fertilization. The theoretical analysis and structure design of its key core components are carried out. The depth of fertilization can be consistent through the established depth control system. The performance test shows that the single spiral ditching and fertilizing machine has a maximum stability coefficient of 96.17% and a minimum of 94.29% in terms of trenching depth, and a maximum of 94.23% and a minimum of 93.58% in terms of fertilization uniformity, meeting the requirements of tea plantation production.
Vanet FDIA Solutions using Blockchain Based IPFS-Trust Management System with ML SVR Model
Authors: Grover Preeti , Prasad Sanjeev Kumar 
Published: January 2023

Abstract
The Internet of Vehicles (IoV) is the next phase in the evolution of vehicular ad hoc networks (VANETs).Multiple types of Smart Networks exists in our surrounding.i.e., Wireless Sensor Networks (WSNs), Crowd Sensing Networks (CSNs), and Internet of Vehicles, etc A VANET is a collection of mobile nodes (vehicles) that share data through ad hoc on-demand connections. Vehicle Tracking is one of the uses of IOV(Internet of Vehicles) and Vehicle Security is one of the major issues for all vehicle owners. On a vehicle, there are various on-board sensors that sense a vehicle’s motion and the surrounding environment. On-board sensors can also warn drivers about approaching vehicles, speeding, and slippery road conditions. The main aim of the paper is to provide solutions for False Data Injection Attack by Integration of Blockchain Based IPFS-Trust Management System with ML SVR Regression Model. Due to Network Assaults and Threats under Vanet System, the safety of the drivers is under stake and Critical. A rogue node can send out erroneous messages, causing unavoidable scenarios. We first filter the received data from Vehicles creating false traffic jam warning messages using the Machine learning SVR Regression Model where data is created and split into train and test data. We used Machine learning supervised algorithm to find whether the vehicle is a legitimate vehicle or an attacker vehicle and the result is validated using the parameters like Accuracy, Loss Rate, Precision, Recall, and F-Test Score. Algorithm Implementation results show that the FDIA attack strategy achieves a better performance than the without using ML algorithm of SVR Regression Model based attack strategy in Predicting the Vanet Security. Also, we studied the various ways to mitigate the impact of false data injection into the network through a compromised node. Users can access the system through DApp, an Ethereum-distributed application, and manage their vehicle data.
Chemical Fractionation of Manganese in Commercial Coffee Samples Originating from Conventional and Organic Growing Systems
Authors: Junior J. B. S. Espinelli , Wesz I. S. , Santos I. A. , Badiale-Furlong E. , Carapelli R. 
Published: January 2023

Abstract
Coffee can be considered an important source of mineral nutrients. Since coffee is normally consumed through infusion, the availability of nutrients is related to the solubility, that is strongly influenced by the cultivation system applied to its production, which can influence the form of minerals are storage in the coffee bean. Coffee development is influenced by nutrient absorption, metabolism and storage. This study investigated the influence of cultivation on these characteristics of conventional and organic commercial coffee. The average concentration for conventional and organic cultivation determined in this study was 45.5 ± 11.2 and 64.7 ± 9.2 mg kg− 1 respectively. This result may be related to soil characteristics, such as acidic pH and reducing environment, favored by organic cultivation and favoring Mn solubilization in the soil solution, leading to greater Mn uptake. Principal component analysis shows differences between organic and conventional samples in the fractionation study. The characterizing fraction of the organic samples was the lipid and all other fractions characterized the conventional samples. This behavior suggests an influence of cultivation on Mn metabolism and storage by coffee. However, despite these observed differences, the average levels of Mn extracted from coffee infusions did not differ significantly between cultivation.
3D modelling and characterisation of ferralitic basement aquifers by combining resistivity, chargeability and remote sensing data in the Messondo area (SW- Cameroon)
Authors: Ngoumou Paul Claude , Yandjimain Justine , Meli’i Jorelle Larissa , Sofo Cheryl Dowel Ameli , Nzeuga Alain Rodrigue , AMOUGOU Olivier Ulrich Igor OWONO , Assembe Stéphane Patrick 
Published: January 2023

Abstract
An investigation combining remote sensing (Landsat 8) images and ground geoelectricity was carried out in order to remedy deficit in water resources in the Messondo area located in the Nyong and Kelle division, Centre Region, Cameroon.in this region, an . The remote sensing results presented respectively as fractures, fracture density and land use maps, allowed the delineation of densely fractured zones of the basement, which are favourable areas for infiltration and hydraulic capture. These zones are used to guide the geophysical work. The ground geoelectricity combined a 4-line DC and IP tomography survey-oriented SE-NW, boreholes and electrical Schlumberger profiling. After data acquisition, the study identified several conductive anomalies mainly due to the iron bearing gneisses of the basement that would be discriminated between zones of water accumulation and zones of mineralogical concentration. . . The 2D inverse modelling of the geoelectric data depicted the vertical and lateral variations of resistivity and chargeability. The joint analysis of the of these two parameters, combined with the geological observations from the area, allowed the discrimination between the aquifers and the mineralised zones. The 3D models obtained by combining the 2D models then interpolating, permitted to visualise and quantify the aquifers identified in the investigated area. . These models make it possible to distinguish two levels of water accumulation : the first level, spreading over the entire surface, is contained in the porous alterites and forms the surface aquifers that extend to a depth of 39 m, thus defining the thickness of the altered layer. The second level exclusively located to the east of the area, is contained in the fissured gneissic formations.
Degradation of 1,1,2 trichloroethane by photocatalysis using Fe2O3/SPS photocatalyst
Authors: Farouq Rania , Ullah Najeeb 
Published: January 2023

Abstract
Once released into the environmenOnce released into the environment, engineered nanomaterials can significantly influence the fate of organic contaminants. So far, nothing is known about the capability of composite nanomaterials to accelerate the abiotic transformation processes of organic pollutants that are relevant to the environment. Under benign conditions, it is possible to successfully sulphonate recycled commercial polystyrene to boost its surface functionalities and enable the manufacturing of composites through interactions between the surface functional groups and nanoparticles. The porous R-Fe2O3 nanorods were successfully obtained by calcining the R-FeOOH precursors at 300°C for 2 h. In this study, a photocatalytic system composed of α-Fe2O3 and SPS was applied in 1, 1, 2 trichloroethane degradation. Hence, the α-Fe2O3/SPS composite has great potential for sustainable and efficient photocatalytic disinfection applications. The structural and magnetic properties of R- Fe2O3 nanoparticles were confirmed using the results of morphology tests including Fourier-transform infrared spectra, particle size analysis, and transmission electron microscope.
Impact of long-term floods on spatial dynamics of Myrmica scabrinodis, a host ant of a highly threatened Scarce large blue (Phengaris teleius)
Authors: Močilar Mitja , Jerina Klemen , Verovnik Rudi 
Published: January 2023

Abstract
Extensively used humid meadows, with high biodiversity are under threat in Europe due to anthropogenic pressure. Increasing frequency of prolonged floods is emerging as an additional threat to this fragile environment. In our study, we explored how prolonged floods impact the spatial distribution and its dynamic over time (caused by mortality and recolonization process) of the host ant species Myrmica scabrinodis, essential for the survivor of the threatened Scarce large blue (Phengaris teleius). The study was conducted on flood prone area Ljubljansko Barje at the southern edge of the P. teleius global range. Long-lasting floods in the study area, potentially affecting the past and recent distribution of the host ant M. scabrinodis, were recorded in 2010, 2013, and 2017. In 2020, we set up 160 ant traps to estimate host ant distribution in a system of meadows covering entire gradient of history of floods. Our results indicate that M. scabrinodis survive the flooding for up to three days and start to disappear if flooding persists longer. After the flood withdrawal, the ants gradually recolonize empty habitats from the surrounding upland refuge areas. Our spatial analyses predict that the average recolonization speed was about 29 meters per year, and that in one year of recolonization ants compensate the mortality effects of 1.8 days of flooding. These findings elucidate that flooding should be considered as an additional (in some areas a major) threat to the endangered Scarce large blue through its detrimental effects on the host ant species.
Iron Oxide Nanoparticles as Positive T1 Contrast Agents for Low-Field Magnetic Resonance Imaging at 64 mT
Authors: Oberdick Samuel , Jordanova Kalina , Lundstrom John , Parigi Giacomo , Poorman Megan , Zabow Gary , Keenan Kathryn 
Published: January 2023

Abstract
We have investigated the efficacy of superparamagnetic iron oxide nanoparticles (SPIONs) as positive T1 contrast agents for low-field magnetic resonance imaging (MRI) at 64 millitesla (mT). Iron-oxide based agents, such as the FDA-approved ferumoxytol, were measured using a variety of techniques to evaluate T1 contrast at 64 mT. Additionally, we characterized monodispersed carboxylic acid-coated SPIONs with a range of diameters (4.9 nm to 15.7 nm) in order to understand size-dependent properties of T1 contrast at low-field. MRI contrast properties were measured using 64 mT MRI, magnetometry and nuclear magnetic resonance dispersion (NMRD). We also measured MRI contrast at 3 T to provide comparison to a standard clinical field strength. SPIONs have the capacity to perform well as T1 contrast agents at 64 mT, with measured longitudinal relaxivity (r1) values of up to 67 L mmol− 1 s− 1, more than an order of magnitude higher than corresponding r1 values at 3 T. The particles exhibit size-dependent longitudinal relaxivities and outperform a commercial Gd-based agent (gadobenate dimeglumine) by more than eight-fold at physiological temperatures. Additionally, we characterize the ratio of transverse to longitudinal relaxivity, r2/r1 and find that it is ~ 1 for the SPION based agents at 64 mT, indicating a favorable balance of relaxivities for T1-weighted contrast imaging. We also correlate the magnetic and structural properties of the particles with models of nanoparticle relaxivity to understand generation of T1 contrast. These experiments show that SPIONs, at low fields being targeted for point-of-care low-field MRI systems, have a unique combination of a large moment plus water-diffusion correlation times close to the proton precession period, that provide very large T1 relaxivities.
Dark Sky Parks: Public Policy that Turns off the Lights
Authors: Alva Amanda , Brown Eric , Evans Aaron , Morris Daniel , Dunning Kelly 
Published: January 2023

Abstract
A clear view of the night sky is rare, as over 80% of the world’s population cannot see the Milky Way Galaxy at night. Dark skies are culturally, ecologically, and economically valuable natural resources. Over the past twenty years, policies for stopping light pollution have increased around the world. This research asks how dark sky conservation is being enacted in the United States. Using the Multiple Streams Framework and qualitative data from over 300 policy documents, we characterize the problems, policy solutions, and politics around protecting night sky resources. We find that the problem with diminishing night skies is that of light pollution from urban development, especially in Western communities growing exponentially after the Covid-19 pandemic. To address the problem, the most important policy solution is the creation of Dark Sky Parks, a rigorous and scientific process articulated by a non-governmental organization known as the International Dark-Sky Association (IDA). The IDA’s technical ideas for creating Dark Sky Parks are transmitted to decision-makers at park and landscape scales, as well as to individual members of the public to create policy change. The political backdrop of dark sky conservation entails surprising bipartisan support from policy-makers from different political parties due to the economic potential of astrotourism. Our findings are important for understanding how one country is protecting its night skies, as there are many possible pathways to conserving this natural resource. Our work has general applications for the role of NGOs in creating science policy, engaging the public, and enacting policy change.
Effects of inorganic arsenic on type 2 diabetes mellitus in vivo: The roles and mechanisms of miRNAs
Authors: Sira Jackson , Zhang Xiaodan , Gao Lin , Wabo Therese Martin Cheteu , Li Jinyu , Akiti Caselia , Sun Dianjun , Zhang Wei 
Published: January 2023

Abstract
Accumulating studies have shown that chronic exposure to iAs correlates with an increased incidence of diabetes. In recent years, miRNA dysfunction has emerged both as a response to iAs exposure and independently as candidate drivers of metabolic phenotypes such as T2DM. However, few miRNAs have been profiled during the progression of diabetes after iAs exposure in vivo. In the present study, high iAs (10 mg/L NaAsO2) exposure mice models of C57BKS/Leprdb (db/db) and C57BLKS/J (WT) were established through the drinking water, the exposure duration was 14 weeks. The results showed that high iAs exposure induced no significant changes in FBG levels in either db/db or WT mice. FBI levels, C-peptide content and HOMA-IR levels were significantly increased, and glycogen levels in the livers were significantly lower in arsenic-exposed db/db mice. HOMA-β% was decreased significantly in WT mice exposed to high iAs. In addition, more different metabolites were found in the arsenic-exposed group than the control group in db/db mice, mainly involved in the lipid metabolism pathway. Highly expressed glucose, insulin, and lipid metabolism-related miRNAs were selected, including miR-29a-3p, miR-143-3p, miR-181a-3p, miR-122-3p, miR-22-3p and miR-16-3p. And a series of target genes were chosen for analysis, such as ptp1b, irs1, irs2, sirt1, g6pase, and pepck. The results showed that, the axles of miR-181a-3p-irs2, miR-181a-3p-sirt1, miR-22-3p-sirt1, and miR-122-3p-ptp1b in db/db mice, and miR-22-3p-sirt1, miR-16-3p-glut4 in WT mice could be considered as promising targets to explore the mechanisms and therapeutic aspects of T2DM after exposure to high iAs.
Machine Learning Algorithm Using Classification and Regression Trees, Linear Gaussian Naive Bayes, Support Vector Machines, Cart and K-nearest Neighbors to Aid Cancer Research Firms in Data Grouping and Better Analysis
Authors: Ndungi Rebeccah 
Published: January 2023

Abstract
World Health Organization publications disclose that breast cancer is one of the most common diseases amongst the women, and that it has a high death rate. Its prevalence is growing in developing nations, where the vast majority of cases are discovered late in the disease's development. Preventing this malignancy may be accomplished with safeguards and frequent examinations. Aside from that, early detection of the illness may be beneficial in terms of battling the condition. This deep learning algorithm is a strong approach for identifying features about the breast mass that are often not visible to the human eye through deep learning analysis of the mammogram. The algorithm will then be evaluated through various metrics to validate on its accuracy. Deep learning is a technology that will be used in this project. The algorithm intends to help cancer firm research centres in Kenya and globally in quicker grouping, identification and aid doctors in quicker diagnosis and research.
Occupancy Models with Autocorrelated Detection Heterogeneity
Authors: Hepler Staci , Yang Biqing 
Published: January 2023

Abstract

Occupancy models are commonly used in statistical ecology to model binary detection/non-detection data. These hierarchical models make a distinction between detection/non-detection and presence/absence by treating true occupancy as a latent process. In this paper, we propose a multi-species, multi-season occupancy model to jointly model detection/non-detection data on multiple species. Existing literature has shown that models which account for various sources of dependence in the latent occupancy process improve estimation, especially in the single-survey setting. However, the detection process in the model has not received much attention, even though detectability of a species is expected to relate to the detectability of other species and to detectability in previous time periods. In this work, we propose a model to capture this phenomenon by incorporating a multivariate temporal random effect in the detection process. We perform a simulation study to show that the proposed model yields more accurate estimates of regression effects and probabilities as compared to models that only use covariates to quantify detection. We apply our model to detection/non-detection data on three species – Thomson’s gazelle, zebra, and wildebeest – in Serengeti National Park of Tanzania, Africa.
Interest in PrEP and Impact of a Brief Educational Intervention Among Attendees of General Obstetrics &amp; Gynecology Clinics in New Orleans, Louisiana
Authors: Naresh Amber 
Published: January 2023

Abstract
Introduction: We sought to determine if an educational intervention about HIV risk alters HIV risk self-perception and interest in Pre-Exposure Prophylaxis (PrEP) in Obstetrics & Gynecology clinics.
Methods: Demographic information, risk behaviors, HIV knowledge and risk self-assessment were collected via a self-administered survey. Participants viewed a written educational intervention and completed a post-intervention survey. HIV risk self-perception and interest in PrEP were compared before and after the intervention.
Results: 170 participants were included. 85 of participants (50.0%) were interested in PrEP at baseline. Pre-intervention HIV risk self-perception was associated with interest in PrEP (p=0.01). After administration of the educational intervention, knowledge of risk factors and the number of those who perceived themselves to be at risk of HIV increased (p<0.01), but the intervention did not significantly alter interest in PrEP.
Conclusions: Interest in PrEP was associated with HIV risk self-perception and a written educational intervention increased knowledge of HIV risk factors.
Evaluation of immunity enhancing potential of Ocimum sanctum L. (TulsiOdaat™) on mouse macrophage RAW 264.7 cells, network pharmacology and insilico studies
Authors: Tamoli Sanjay , Chandra Naveen , U Vishwanatha , Khatau Kiran 
Published: January 2023

Abstract
Tulsi (Ocimum sanctum Linn), commonly known as Holy Basil, has traditionally been used as a remedy for common infections of the respiratory tract, and as an immunity booster. The herb has potential anti-microbial, anti-bacterial, and anti-viral effects. The present study evaluated the cytotoxic and phagocytic activity of a standardized extract of Ocimum sanctum (TulsiOdaat™) in mouse macrophages RAW 264.7 cell lines. Phagocytic activity was evaluated by observing the amount of engulfed zymosans isolated from yeasts at 405 nm. The study demonstrated that TulsiOdaat™ significantly enhanced the phagocytic activity of macrophages compared to the vehicle-treated/control group at a non-toxic concentration of 3 µg/mL. The observations made in the present study confirm that TulsiOdaat™ stimulates macrophages and enhances their phagocytic activity and therefore, may have potential enhancing effects on innate immunity. Moreover, the elected target proteins showED strong correlation to each other including such as CASP3 and MAPK. Interestingly, insilico docking of ursolic acid have strong binding affinity to CASP3 and MAPK as well as SARS-CoV-2 proteins. The in-vitro and in-silico studies revealed that bioactive compounds of Ocimum sanctum may augment the immune response against foreign antigens or disease-causing pathogens.