bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physicochemical characteristics and seasonal variations of PM 2.5 in urban, industrial, and suburban areas in South Korea
Authors: Hwang Kyucheol , Kim Jeongho , Lee Jae Young , Park Jong-Sung , Park Sechan , Lee Gahye , Kim Chang Hyeok , Kim Pilho , Shin Su Hyun , Lee Kwang Yul , An Joon-Young , Park Jungmin , Kim Jong Bum 
Published: June 2023

Abstract
Among the Organization for Economic Co-operation and Development (OECD) countries, South Korea has the highest population exposure to PM2.5. Although the country’s diverse PM2.5 reduction policies have improved the pollution levels, the PM2.5 concentrations still pose serious environmental and health risks. Herein, we monitored the physicochemical components, such as ion, metal, organic carbon/ elemental carbon (OC/EC), and particle number concentrations, across different regions in South Korea for January 1–December 31, 2021. The study area consisted of the city center, industrial complexes, and suburban areas. Before analyzing the emission characteristics of each site, we compared the Clean Air Policy Support System (CAPSS) data for the three areas, to analyze the main emission sources. The annual particle number concentrations for the three areas were 21.8–26.44 µg/m3; the maximum values were evident in March. All the three areas portrayed high ratios of NO3− with different components in all seasons. The particle number concentrations in the three sites were 1.3–1.5 × 107, and the peak points of the concentrations were different in every site: city center (40 nm), industrial complexes (60 nm), and suburban areas (80 nm). We also conducted potential source contribution function (PSCF) and conditional bivariate probability function (CBPF) analyses, to determine the inflow direction of the pollution sources, for high PM2.5 episodes. For the episodes that occurred in spring and winter, there were no differences in the PM2.5 concentrations between the three sites. This study can serve as a framework for developing air-quality management policies in South Korea.
Establishment and validation of a nomogram containing cytokeratin fragment antigen 21-1 for the differential diagnosis of intrahepatic cholangiocarcinoma and hepatocellular carcinoma
Authors: Liu Yuan-Yuan , Li Yue-Yue , Liu Yong-Shuai , Zhang Zong-Li , Gao Yan-Jing 
Published: June 2023

Abstract
Background
Our study aimed to develop a nomogram, including cytokeratin fragment antigen 21 − 1 (CYFRA21-1) to aid in the differential diagnosis of patients with intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC).
Methods
This study included a total of 487 patients diagnosed with ICC and HCC at Qilu Hospital of Shandong University. They were further divided into a training cohort and a validation cohort based on whether the data was collected retrospectively or prospectively. Univariate and multivariate analyses were used to select variables for the nomogram. The discrimination and calibration of the nomogram were assessed using the area under the receiver operating characteristic curve (AUC) and calibration plots. The net benefits of the nomogram at different threshold probabilities were evaluated using decision curve analysis (DCA).
Results
Six variables, including CYFRA21-1, were selected to establish the nomogram. A satisfactory discriminative ability of the nomogram was indicated by AUC (0.979 of training cohort, 0.991 of validation cohort). Hosmer-Lemeshow test and the calibration plots showed favorable consistency between the prediction of the nomogram and actual observations. Furthermore, DCA demonstrated that the nomogram was clinically useful and had better discriminative ability than the model without CYFRA21-1 and the model consisted of logarithm of alpha-fetoprotein (Log AFP) and logarithm of carbohydrate antigen 19–9 (Log CA19–9).
Conclusions
This study developed and validated a nomogram, including CYFRA21-1 that can assist clinicians in the differential diagnosis of ICC and HCC in patients.
Altered Rbfox1-Vamp1 pathway and prefrontal cortical dysfunction in schizophrenia
Authors: Chung Youjin , Dienel Samuel , Belch Matthew , Fish Kenneth , Ermentrout George , Lewis David , Chung Daniel 
Published: June 2023

Abstract
Deficient gamma oscillations in prefrontal cortex (PFC) of individuals with schizophrenia appear to involve impaired inhibitory drive from parvalbumin-expressing interneurons (PVIs). Inhibitory drive from PVIs is regulated, in part, by RNA binding fox-1 homolog 1 (Rbfox1). Rbfox1 is spliced into nuclear or cytoplasmic isoforms, which regulate alternative splicing or stability of their target transcripts, respectively. One major target of cytoplasmic Rbfox1 is vesicle associated membrane protein 1 (Vamp1). Vamp1 mediates GABA release probability from PVIs, and the loss of Rbfox1 reduces Vamp1 levels which in turn impairs cortical inhibition. In this study, we investigated if the Rbfox1-Vamp1 pathway is altered in PVIs in PFC of individuals with schizophrenia by utilizing a novel strategy that combines multi-label in situ hybridization and immunohistochemistry. In the PFC of 20 matched pairs of schizophrenia and comparison subjects, cytoplasmic Rbfox1 protein levels were significantly lower in PVIs in schizophrenia and this deficit was not attributable to potential methodological confounds or schizophrenia-associated co-occurring factors. In a subset of this cohort, Vamp1 mRNA levels in PVIs were also significantly lower in schizophrenia and were predicted by lower cytoplasmic Rbfox1 protein levels across individual PVIs. To investigate the functional impact of Rbfox1-Vamp1 alterations in schizophrenia, we simulated the effect of lower GABA release probability from PVIs on gamma power in a computational model network of pyramidal neurons and PVIs. Our simulations showed that lower GABA release probability reduces gamma power by disrupting network synchrony while minimally affecting network activity. Finally, lower GABA release probability synergistically interacted with lower strength of inhibition from PVIs in schizophrenia to reduce gamma power non-linearly. Together, our findings suggest that the Rbfox1-Vamp1 pathway in PVIs is impaired in schizophrenia and that this alteration likely contributes to deficient PFC gamma power in the illness.
Catalytic Hydrocracking of Jatropha Oil for Bio-jetfuel Production using natural clay
Authors: Hisham Sarah , Kamal Nahed , Diwani Guzine El , Kamel Shereen , Ettouney Reem , El-Rifai Mahmoud 
Published: June 2023

Abstract
Biofuels such as biodiesel and bio-jet fuel are‏ important sources of renewable energy, which has to be added to petroleum fuels in different ratios for environmental purposes. Biofuels in general, can be produced from several raw agriculture materials. Currently, the most important biofuel is the bio-jet fuel, used for partial replacement of jet fuel from petroleum origin. The most promising method for bio-jet fuel manufacture is the catalytic hydrocracking of a low-cost raw vegetable oil such as non-edible Jatropha oil. The type of product and its quality and quantity depend on the process conditions such as reaction time, temperature, and catalyst type, form, and amount. Heterogeneous catalysts play an important role in this process. The present study aims to the production of bio-jet fuel by hydrocracking of Jatropha oil conforming to ASTM specifications by the selection and preparation of an economic inorganic catalyst. The 4% catalyst was used in the production of biojet fuel under the obtained optimum operating conditions of 350˚C, 4 bar H2, 18 min, and followed by fractionation tower. The products were tested and their specifications conformed to the ASTM specifications, viz the freezing point (-56˚C), the flash point (53˚C), and existent gum content (5.9 mg/100 ml).
Effect of tungsten carbide reinforcement phase on the abrasive wear performance of metal matrix composites deposited by laser cladding
Authors: Panziera Renato Camponogara , Pereira Milton , Castro Richard de Medeiros , Curi Elvys Isaías Mercado , Neto Flavio Guedin 
Published: June 2023

Abstract

One of the biggest challenges facing industrial sectors such as agriculture, mining, oil and gas, and aerospace today is issues related to component wear. In this context, the laser cladding process has often been chosen as a deposition process for abrasion resistant coatings due to the low dilution and microstructural characteristics found in the deposited material. An option for improving abrasion resistance has been the use of reinforcement phases from carbides. However, it is necessary to have a comparative study of the tribological performance of deposits made with different metallic matrices and different proportions of reinforcements. The state of the art indicates the lack of a detailed tribological study of Metal Matrix Composites (MMC) using the chemical composition of the metallic matrices in this study, as well as the high proportion of tungsten carbide (WC), as a reinforcement element, applied to the ASTM G65 standardized test. Laser processing parameters, hardness and abrasive wear performance were studied by changing the volume fraction of WC by 0, 20 and 30%Vol. in two nickel-based metallic matrices and one iron-based matrix deposited via laser cladding. The results indicate that the increase in the fraction of WC in the metallic matrix provides a smaller volumetric loss and greater resistance to abrasion reaching a volumetric loss of up to 95% lower when compared to the composite material with the matrix in its pure state. This resistance is also related to the microhardness and anchoring performance of the hard WC particles on each metallic matrix. However, there is a processability limit when using a high percentage of reinforcement phase, generating chemical and thermal reactions in the metallic matrix, causing structural defects in the deposited composite coating. In addition, the different mechanisms of abrasive wear are influenced by the hardness and the change in the chemical composition of the metallic matrix, which can lead to adhesive and brittle wear, generating greater volumetric losses during the abrasive test.
Functional Architecture of Brain and Blood Transcriptome Delineate Biological Continuity Between Suicidal Ideation and Suicide
Authors: Sun Shengnan , Liu Qingkun , Wang Zhaoyu , Huang Yung-yu , Sublette M. , Dwork Andrew , Rosoklija Gorazd , Ge Yongchao , Galfalvy Hanga , Mann J. John , Haghighi Fatemeh 
Published: June 2023

Abstract
Human genetic studies indicate that suicidal ideation and behavior are both heritable. Most studies have examined associations between aberrant gene expression and suicide behavior, but behavior risk is linked to severity of suicidal ideation. Through a gene network approach, this study investigates how gene co-expression patterns are associated with suicidal ideation and severity using RNA-seq data in peripheral blood from 46 live participants with elevated suicidal ideation and 46 with no ideation. Associations with presence and severity of suicidal ideation were found within 18 and 3 co-expressed modules respectively (p < 0.05), not explained by severity of depression. Suicidal ideation presence and severity-related gene modules with enrichment of genes involved in defense against microbial infection, inflammation, and adaptive immune response were identified, and tested using RNA-seq data from postmortem brain that revealed gene expression differences in suicide decedents vs. non-suicides in white matter, but not gray matter. Findings support a role of brain and peripheral blood inflammation in suicide risk, showing that suicidal ideation presence and severity is associated with an inflammatory signature detectable in blood and brain, indicating a biological continuity between ideation and suicidal behavior that may underlie a common heritability.
Modeling low flows by univariate hybrid wavelet-time series approach
Authors: MohammadiFard Sheyda , Eslamian Saeid , Modarres Reza 
Published: June 2023

Abstract

This research addressed the forecast of 7-day and 30-day low flows using daily flow data at two hydrometric stations of Qaleh-Shahrokh and Eskandari in Isfahan province, Iran. The two methods of ordinary time series modeling and time series modeling with the help of wavelet (wavelet-time series) are used to forecast low flows. The research also employs the wavelet method as a modern and effective way for the analysis of hydrological time series. In the wavelet-time series modeling, the target time series is decomposed into five levels using the Haar wavelet theory. With this decomposition, the series is divided into two parts including approximation a, which is the main nature of the data, and detail sub-series, which includes the white noise of the data. Then, the time series modeling steps are implemented for the approximation a. The results of the forecast of 7-day and 30-day low flow using the time series and wavelet-time series methods are explored by the error assessment criteria including the coefficient of correlation between the predicted and observed values, root mean squared error (RMSE), and mean absolute deviation (MAD). Finally, the coefficients of correlation between the predicted and observed values of 7-day and 30-day low flows in the Qaleh-Shahrokh and Eskandari stations are estimated at 0.87, 0.87, 0.55, and 0.95 by the time series method and 0.99, 0.99, 0.99, and 0.99 by the wavelet-time series method, respectively. The results show that the wavelet-time series method outperforms the time series method in predicting 7-day and 30-day low flows.
The relationship between nomophobia and psychological distress in Tunisian students: The moderating effect of physical activity
Authors: mechraoui Oumaima , Jelleli Hilmi , Fekih-Romdhane Feten , Rebhi Mahmoud , Saidane Mouna , Guelmami Noomen , Aissa Mohamed Ben , Chater Walid , Bonsaksen Tore , Dergaa Ismail 
Published: June 2023

Abstract

Background Due to their stage of life and the daily stressors they encounter, students are particularly susceptible to both behavioral and psychological issues. Our study was designed with two objectives in mind: (1) to explore the potential mitigating effect of physical activity on the relationship between nomophobia and distress in students; and (2) to evaluate the reliability and validity of the Arabic version of the Depression, Anxiety, and Stress Scales (DASS-12). Methods A cross-sectional analysis was undertaken with a sample of Tunisian students who regularly use smartphones (N = 533, 64.6% female, mean age 25.03 ± 6.55 years). Results The exploratory and confirmatory factor analyses pointed to the DASS-12 as a secondary 3-factor scale. The internal consistency of the scale, as measured by Cronbach’s alphas, was 0.98 for stress, 0.90 for anxiety, and 0.84 for depression. The results of the measurement model supported the suitability and reliability of all the DASS-12 items in capturing the underlying constructs. Structural model analysis revealed positive correlations between physical activity and nomophobia with stress, anxiety, and depression. Moreover, physical activity was found to moderate the relationship between nomophobia and two elements of distress: stress and anxiety. Conclusion The findings of this study open up novel intervention strategies for students grappling with nomophobia. In particular, the results suggest that promoting physical activity might serve as a coping strategy to counteract the impacts of nomophobia on stress and anxiety symptoms in students.
Tissues Macro-Minerals Changes of Growing Camels (Camelus dromedarius) by Regions, in Spring Season of Saudi Arabia
Authors: Matar Abdulkareem , Abdelrahman Mutassim M. , Alhidary Ibrahim A. , Al-Badwi Mohammed A. , Alobre Mohsen M. , Aljumaah Riyadh S. 
Published: June 2023

Abstract
The aim of our study was to evaluate the calcium (Ca), phosphorus (P), and magnesium (Mg) status of slaughtered camel tissues in five regions in Saudi Arabia during the spring season. Selected tissues (whole blood, liver, meat, rumen tissue and rumen fluid samples) were collected from 33 growing camels (one year old) from local slaughterhouses in five regions. Ninety-three biological samples were collected and prepared for analysis for Ca, P and Mg by ICP-MS. A significant variation was reported for the Ca, P, Mg and inorganic content of the liver by region. In meat samples, camels from northern and central regions had significantly higher levels of Ca (P < 0.05), P (P < 0.001), Mg (P < 0.001), and inorganic matter content (P < 0.001) compared to others. A significant variation in Ca, P and Mg concentration was reported in rumen fluid, rumen tissue and whole blood for camels in the eastern region compared to the central region. A negative trend correlation between rumen fluid P and rumen tissue P (r = -0.899; P < 0.10). In summary, variation in the Ca, P, and Mg status of camels affected by regions can result from the differences in their concentration in soil, water, and forage, which are mainly related to environmental factors. Phosphorus is the only macro mineral that has shown a correlation between rumen fluid and rumen tissue. Further research is needed to examine mineral metabolism and the possibility of developing a supplementation program in some regions.
Development and Validation of a Novel liquid-liquid phase separation Gene Signature for Bladder Cancer
Authors: Guo Sufan , Su Qisheng , Yang Zheng , Mo Wuning 
Published: June 2023

Abstract
Background Bladder carcinoma (BLCA) is a prevalent malignancy in the urinary tract and is known for its aggressive nature and high probability of recurrence. The regulation of the biological response during tumor proliferation and metastasis is inextricably linked to liquid-liquid phase separation (LLPS). To facilitate early detection and treatment, this study utilized transcriptomic data to explore the prognostic roles of LLPS-linked genes and develop a predictive model.Methods The dataset of bladder cancer patients consisted of clinical and transcriptomic data retrieved from the GEO and TCGA databases. The study utilized a clustering algorithm that employed non-negative matrix factorization (NMF) to classify the samples, which were further compared systematically for their liquid-liquid phase separation characteristics. A multivariate Cox regression model and the Least Absolute Shrinkage Selection Operator (LASSO) algorithm were utilized to construct prognostic models to establish risk formulas for nine genes. Validation of the gene signature was conducted in the entire TCGA cohort (406 cases), TCGA testing cohort (120 cases), and the external validation dataset GSE13507. The signature system was evaluated using both receiver operating characteristic (ROC) and Kaplan-Meier curves. Furthermore, decision curve analysis including the clinicopathological parameters and genetic signature was utilized to predict individual survival.Results In the study, two distinct molecular subtypes were identified, namely C1 and C2. It was revealed that individuals with the C1 subtype had a significantly more favorable prognosis as compared to those with the C2 subtype. Patients belonging to the low-risk group had remarkably better prognoses compared to those in the high-risk groups across the entire TCGA, GEO, and TCGA training cohorts. In addition, the LLPS-related gene model constructed in the study was validated as a prognostic factor independent of other clinical traits.Conclusions This study identifies gene clusters associated with LLPS and establishes a model that can predict, accurately and independently, the prognosis of BLCA. This model can be utilized in clinical practice to assess the prognosis of BLCA.
Toxic elements determination in selected cosmetic products: Health risk assessment
Authors: Đogo-Mračević Svetlana , Laketić Tatjana , Stanković Milan , Lolić Aleksandar 
Published: June 2023

Abstract

The aim of this research was to determine the content of arsenic (As), cadmium (Cd), lead (Pb), and nickel (Ni) in selected lipsticks and face foundations of different countries of origin and price categories, as well as the assessment of health risk associated with these metals via dermal and oral exposure. The samples were prepared by acid digestion and then analyzed by flame atomic absorption spectroscopy (FAAS) – Cd, Pb and Ni and electrothermal atomic absorption spectrometry (ETAAS) – As. Arsenic was found in 50% of lipstick samples and in only two face foundation samples with the highest concentration of 0.28 mg/kg in the lipstick sample, the lead concentration was in the range of 1.15 to 5.12 mg/kg in ten samples. Nickel was found in five samples out of 20, with the highest concentration of 4.20 mg/kg. Cadmium was found in only one face foundation sample in the cheaper price range (1.11 mg/kg). The obtained results indicate that concentrations of As, Pb, Cd, and Ni were within the permissible limits according to Serbian legislation. Health risk associated with these elements was assessed as non-carcinogenic and carcinogenic risk. Obtained hazard quotients (HQs) and hazard indexes (HIs) were below 1, indicating the absence of significant non-carcinogenic health risk due to exposure to these TEs. The carcinogenic risk results show that investigated cosmetic products can be considered low–risky due to the possibility of causing malignant disease.
Surface Quality Prediction by Machine Learning Methods and Process Parameter Optimization in Ultra-Precision Machining of AISI D2 Using CBN tool
Authors: Adizue Ugonna Loveday , Tura Amanuel Diriba , Isaya Elly Ogutu , Farkas Balázs , Takács Márton 
Published: June 2023

Abstract
High-quality machining is a crucial aspect of contemporary manufacturing technology due to the vast demand for precision machining for parts made from hardened tool steels and super alloys globally in the aerospace, automobile, and medical sectors. The necessity to upheave production efficiency and quality enhancement at minimum cost requires deep knowledge of this cutting process and development of machine learning-based modeling technique, adept in providing essential tools for design, planning, and incorporation in the machining processes. This research aims to develop a predictive surface roughness model and optimize its process parameters for Ultra-precision hard-turning finishing operation. Ultra-precision hard-turning experiments were carried out on AISI D2 of HRC 62. The response surface method (RSM) was applied to understand the effect of process parameters on surface roughness and carry out optimization. Based on the data gained from experiments, Machine learning models and algorithms were developed with Support vector machine (SVM), Gaussian process relation (GPR), Adaptive-neuro fuzzy inference system (ANFIS), and artificial neural network (ANN) for the prediction of surface roughness. The results show that ANFIS gave the best predictive accuracy of average R, RMSE, and MAPE values of 0.98, 0.06, and 9.98%, respectively, and that of additional validation tests were 0.81, 0.17 and 32.34%, respectively, which are found reasonably accurate. The RSM analysis shows that the feed is the most significant factor for minimizing surface roughness Ra among the process parameters, with 92% influence, and optimal cutting conditions was found to be cutting speed = 100 m/min, feed = 0.025 mm/rev and depth of cut = 0.09 mm, respectively. This finding can be helpful in the decision-making on process parameters in the precision machining industry.