bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pollution characteristics and health risk assessment of PM2.5 bound PAHs during heating season in industrial urban area of Jinan City, China
Authors: Wang Yan , Gao Yanxin , Yu Zhigang , Liu Qiang , Li Renbo , Wu Xingbin , Du Yinglin , Sui Shaofeng 
Published: September 2023

Abstract
This study was aimed to analyze temporal trends, pollution sources and carcinogenic health risks of atmospheric PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) from the northeastern industrial urban area of Jinan city in the heating season. A total of 245 PM2.5 samples were collected during the heating season from Nov. 2014 to Mar. 2021. The average daily concentrations of Σ16PAHs ranged from 0.25 ng∙m− 3 to 733.69 ng∙m− 3, with an overall trend of increasing firstly and then decreasing gradually. Human health risk assessments of respiratory exposure to PAHs in PM2.5 were conducted by using probabilistic method from the United States Environmental Protection Agency (USEPA). The main sources of PAHs are diesel, gasoline, coal, vehicles and industrial furnaces. The 95th percentile of lifetime carcinogenic risks of Σ16PAHs ranged from 0.43×10− 6 to 2.84×10− 6. The differences between cancer risks of PAHs in different heating seasons were of statistically significant (P < 0.001). Higher cancer risks of PAHs exposure were presented from winter 2015 to spring 2016. After 2017, the cancer risks of PAHs to population were below the acceptable level of 1× 10− 6.
Averaging for stochastic perturbations of integrable systems
Authors: Huang Guan , Kuksin Sergei , Piatnitski Andrey 
Published: September 2023

Abstract

We are concerned with averaging theorems for $\eps$-small stochastic perturbations of integrable equations in $\R^d \times \T^n =\{(I,\f)\}$
$$\dot I(t) =0, \quad \dot \f(t) = \theta(I), \eqno{ (1)}$$
and in $\R^{2n} = \{ v=(\bv_1, \dots, \bv_n), \ \bv_j \in \R^2\}$,
$$\dot\bv_k(t) =W_k(I) \bv_k^\perp, \quad k=1, \dots, n, \eqno{ (2)}$$
where $I=(I_1, \dots, I_n)$ is the vector of actions, $I_j = \frac12 \| \bv_j\|^2$.The vector-functions $\theta$ and $W$ are locally Lipschitz and non-degenerate. Perturbations of these equations are assumed to be locally Lipschitz and such that some few first moments of the norms of their solutions are bounded uniformly in $\eps$, for $0\le t\le \eps^{-1} T$. For $I$-components of solutions for perturbations of (1) we establish their convergence in law to solutions of the corresponding averaged $I$-equations, when $0\le \tau := \eps t\le T$ and $\eps\to0$. Then we show that if the system of averaged $I$-equations is mixing, then the convergence is uniform in the slow time $\tau=\eps t\ge0$.
Next using these results, for $\eps$-perturbed equations (2) we construct well posed {\it effective stochastic equations} for $v(\tau)\in \R^{2n}$ (independent of $\eps$) such that when $\eps\to0$, the actions of solutions for the perturbed equations with $t:= \tau/\eps$ converge in distribution to actions of solutions for the effective equations. Again, if the effective system is mixing, this convergence is uniform in the slow time $\tau \ge0$.
We provide easy sufficient conditions on the perturbed equations which ensure that our results apply to their solutions.
Tracking and Co-Location of Global Point Clouds for Large-Area Indoor Environments
Authors: Michiels Nick , Jorissen Lode , Put Jeroen , Liesenborgs Jori , Vandebroeck Isjtar , Joris Eric , Reeth Frank Van 
Published: September 2023

Abstract

Extended Reality (XR) experiences are on the verge of becoming widely adopted in diverse application domains. An essential part of the technology is accurate tracking and localization of the headset to create an immersive experience. A subset of the application domains requires perfect co-location between the real and the virtual world, where virtual objects are aligned with real-world counterparts. Current headsets support co-location for small areas, but suffer from drift when scaling up to larger ones such as buildings or factories. This paper proposes tools and solutions for this challenge by splitting up the simultaneous localization and mapping (SLAM) into separate mapping and localization stages. In the pre-processing stage, a feature map is built for the entire tracking area. A global optimizer is applied to correct the deformations caused by drift, guided by a sparse set of ground truth markers in the point cloud of a laser scan. Optionally, further refinement is applied by matching features between the ground truth keyframe images and their rendered-out SLAM estimates of the point cloud. In the second, real-time stage, the rectified feature map is used to perform localization and sensor fusion between the global tracking and the headset. The results show that the approach achieves robust co-location between the virtual and the real 3D environment for large and complex tracking environments.
Rational Engineering of Magnetic recyclable S-scheme FeS 2 /TiO 2 heterojunction for photocatalytic destruction of rhodamine B dye under full broad spectrum
Authors: Alsalme Ali , Nabeh Nagy , Hasan Mohamed , Abdel-Messih M. F. , sultan Ayman , Ismail mohamed 
Published: September 2023

Abstract
Precise tunable of heterojunctions with strong redox power is future challenge in photocatalytic treatment of wastewater and energy production. The circuit of the heterojunction must carefully built of two semiconductors aligned in band gap structure with large redox potential difference. Sonicated FeS2/TiO2 magnetic heterojunctions containing various proportion of FeS2 [0-10%] are synthesized for expelling rhodamine B dye under solar radiations. Magnetic FeS2 nanoparticles are synthesized through controlled sonochemical route with precise drying under N2-atmosphere to avoid the simultaneous oxidation of Fe2+ to Fe3+ ions. Different compositions of black magnetic FeS2 nanoparticles are deposited sonochemically on TiO2 surface. The nanostructure, crystalline and optical properties of the solid specimens are thoroughly evaluated by HRTEM, BET, Zeta potential measurements, and XRD, PL and DRS techniques. Black magnetic FeS2 nanoparticles are efficiently transfer the absorbability of the heterojunction to deep visible and NIR regions by exceptional reducing the band gap energy of TiO2 from 3.22 to 1.47 eV. The electron-hole recombination is effectively depressed by 50 % as elucidated from PL analysis. The photocatalytic reactivity of FeS2/TiO2 outperformed TiO2 and FeS2 by 1.4 and 1.6 times in removal of RhB dye. Delightfully, 95 % of RhB dye degrades effectively on the heterojunction containing 95 wt % TiO2 and 5 wt % FeS2 during two hours of light illumination compared with 97% removal over pristine titania. This extra-ordinary efficiency is ascribed to impulsive role of FeS2 in elevating the electron-hole transportation and separation. A wealth of S-scheme heterojunction charge transportation mechanism is verified through scrubber trapping experiments and PL measurements of terephthalic acid. The hole-electron pair accumulated in the valence and conduction bands of TiO2 and FeS2 nanoparticles, respectively are the spacious charge carriers consumed in the photodegradation process. In conclusion, magnetic S-scheme FeS2/TiO2 heterojunction can convert full solar absorption spectrum into chemical energy dissipated in destruction of toxic organic dye emerged from different wastewater resources.
Dysregulation of SMURF1 by miR-1292-5p involves in lung adenocarcinoma EMT via BMPR2/p-Smad5 signal pathway
Authors: Liu Dewei , Li Lixia , Xu Zhiyi , Huang Jiawei , Zhao Xuanna , Chen Tingting , Li Dongming , Wu Bin , Liang Zhu , Huang Dan , Wu Dong 
Published: September 2023

Abstract

MicroRNAs have been shown to play a vital role in lung adenocarcinoma (LUAD) progression. In this study, we examined the underlying mechanism and biological functions of miR-1292-5p in LUAD. In LUAD tissues and cell lines, the expression of miR-1292-5p was detected using quantitative real-time polymerase chain reaction. The impact of miR-1292-5p in LUAD cells was assessed both in vitro and in vivo, while the formation of filopodia was analyzed through immunofluorescence staining. Analysis of clinical features revealed the correlation of miR-1292-5p expression and LUAD prognosis. The regulatory relationship of miR-1292-5p and SMURF1 was investigated by dual-luciferase assay and rescue experiment. The signal pathway of epithelial-to-mesenchymal transition was analyzed by western blot. The expression of miR-1292-5p, an upregulated miRNA, was detected in LUAD tissues and cell lines. Its expression showed correlation with the prognosis of LUAD. In vitro and in vivo experiments demonstrated that the overexpression of miR-1292-5p led to the promotion of migration and invasion in LUAD cells. Additionally, it induced the formation of filopodia. Mechanistically, miR-1292-5p targeted SMURF1 to regulate epithelial-to-mesenchymal transition via the BMPR2/p-Smad5 signal pathway in LUAD cells. Our study reveals that dysregulation of SMURF1 targeted by miR-1292-5p influences migration and invasion, and induces epithelial-to-mesenchymal transition by activating the BMPR2/p-Smad5 signal pathway in LUAD.
Breast and cervical cancer screenings across gender identity: results from the Behavioral Risk Factor Surveillance System before and during the COVID-19 pandemic
Authors: Berzansky Isa , Reynolds Colleen , Charlton Brittany 
Published: September 2023

Abstract
Purpose
Although national medical organizations often neglect to include trans and gender diverse (TGD) people in their breast and cervical cancer screening recommendations, the World Profession Association of Transgender Health recommends that TGD people who are at risk for these cancers follow existing guidelines for cisgender women. Despite WPATH’s recommendations, TGD people are less likely to get screened in large part due to discrimination. The COVID-19 pandemic has limited access to cancer screenings among cisgender people, but it is unknown how this has impacted TGD people.
Methods
Using national survey data from the Behavioral Risk Factors Surveillance System (BRFSS), we examined differences in cervical and breast cancer screening noncompliance across gender identity at two time points: before and during the COVID-19 pandemic.
Results
Screening noncompliance increased during the COVID-19 pandemic among cisgender and TGD people (e.g., transmen, gender non-conforming people). Compared to cisgender women, transmen and gender non-conforming respondents had higher odds of breast cancer screening noncompliance before and during COVID-19. Transmen had lower odds of cervical cancer screening noncompliance than cisgender women before COVID-19, but higher odds during the pandemic. Gender non-conforming respondents also had lower odds of cervical cancer screening noncompliance during COVID-19 compared to cisgender women.
Conclusions
Screening noncompliance for breast and cervical cancer was more common among TGD people than cisgender women; while these disparities existed before the COVID-19 pandemic, they were exacerbated during the pandemic. Future work should move beyond descriptive statistics and elucidate underlying causes to inform interventions.
Antifungal Susceptibility Pattern of Candida species Isolated from Pregnant Women in ‎Hajjah City, Yemen
Authors: Edrees Wadhah 
Published: September 2023

Abstract

Background and Aims: Candida species, opportunistic yeast, are the second most common cause of female vulvovaginal candidiasis. This study aimed to evaluate the antifungal susceptibility profile of the isolated Candida species in pregnant women in Hajjah City, Yemen.
Materials and Methods: A hospital-based cross-sectional study was conducted among 396 pregnant women attending Authority AL-Gumhorri Hospital Hajjah between February and July 2023. Vaginal swabs were collected, and Candida species were isolated and identified based on the standard laboratory method. Furthermore, the antifungal drug susceptibility of Candida species was determined by the Kirby-Bauer technique.
Results: The prevalence of vaginal Candida infection among pregnant women was 61.4%. Candida albicans and non-albicans Candida had prevalence rates of 59.26% and 40.74%, respectively. The highest rate of Candida infections was among women aged 24–30 years (71.9%) who finished primary school (77.8%), with the third trimester (80%), multigravida (66.1%), and recurrent infection (67.7%) showing significant differences (P ˂ 0.05). The isolated Candida species revealed susceptibility to ketoconazole (89.7%), amphotericin B (84.8%), miconazole (84.8%), itraconazole (83.5%), and fluconazole (79%). In contrast, 30.5% of Candida species were resistant to clotrimazole. Additionally, approximately 46.2% of isolated Candida albicans exhibited one kind of antifungal drug resistance, whereas 38.7% of isolated non-albicans exhibited resistance to three different antifungal agents.
Conclusion: According to the above findings, Candida infection is highly prevalent in Yemen and quite widespread. Interventions in health education are advised to increase women's knowledge of vaginitis and its prevention. The antifungal susceptibility test may also be helpful in determining the best medication for each patient.
Seismic Anisotropy Assessment based on Machine Learning Approaches
Authors: Zhao Guibin , Bouchaala Fateh , Jouini Mohamed S 
Published: September 2023

Abstract
Estimation of seismic anisotropy parameters such as Thomson’s parameters is crucial in investigating fractured and finely layered geological media. However, most of inversion methods rely on complex physical models with initial assumptions, making the estimate non-reproducible and fracture interpretation subjective. To address these issues, we have proposed three classical machine learning methods and one deep learning algorithm to estimate Thomsen's parameters, namely Support Vector Regression, Extreme Gradient Boost, Multi-layer Perceptron and one-dimensional Convolutional Neural Network. Synthetic data were generated by using earth model by using well data within a finite difference numerical program. After a thorough investigation of synthetic data, amplitudes of direct and reflected waves in time and frequency domain were selected as input features to train machine learning methods. The optimization of machine learning hyperparameters enables the accomplishment of training and testing procedures were reached with high accuracies. Subsequently, the optimized machine learning methods were used to predict Thomsen’s parameters (\({\epsilon }\) and \({\delta }\)) of a shaley formation in the zone area. The estimated \({\epsilon }\) and \({\delta }\) were compared with reference values obtained at well location by using physics-based model. The least relative errors beween reference and machine learning Thomson’s parameters are spanning from 2.92–7.14%.
Analytical solutions of systems of linear retarded and neutral delay differential equations by the Laplace transform: featuring limit cycles
Authors: Kerr Gilbert , Lopez Nehemiah , Gonzalez-Parra Gilberto 
Published: September 2023

Abstract

In this paper we develop an approach for obtaining the solutions to systems of linear retarded and neutral delay differential equations. Our analytical approach is based on the Laplace transform, inverse Laplace transform and the Cauchy residue theorem. The obtained solutions have the form of infinite non-harmonic Fourier series. The main advantage of the proposed approach is the closed-form of the solutions, which are capable of accurately evaluating the solution at any time. Moreover, it allows one to study the asymptotic behavior of the solutions. A remarkable discovery, which to the best of our knowledge has never been presented in the literature, is that there are some particular linear systems of both retarded and neutral delay differential equations for which the solution approaches asymptotically to a limit cycle. The well-known method of steps in many cases is unable to obtain the asymptotic behavior of the solution and would most likely fail to detect such cycles. Examples illustrating the Laplace transform method for linear systems of DDEs are presented and discussed. These examples are designed to facilitate a discussion on how the spectral properties of the matrices determine the manner in which one proceeds and how they impact the behavior of the solution. Comparisons with the exact solution provided by the method of steps are presented. Finally, we should mention that the solutions generated by the Laplace transform are, in most instances, extremely accurate even when the truncated series is limited to only a handful of terms and in many cases becomes more accurate as the independent variable increases.
Physico-chemical and acoustic behaviour of Potassium metabisulphite salts in aqueous medium
Authors: Chanderasekaran J. H. Rakini , Nithiyanantham S. 
Published: September 2023

Abstract
Density, viscosity and ultrasonic velocity through which liquids and liquid mixtures analysed by means of understanding molecular interactions. In the present paper, relaxation time, relaxation amplitude, ultrasonic attenuation, relative association, isentropic compressibility, Vander Waal’s constant, internal pressure, equivalent conductance, cohesive energy barrier, molar volume, molar solvation number and some related parameters for aqueous solution of potassium metabisulphite at different concentration and temperature ranges have been estimated through velocity measurements at 2 MHz frequency. There has also been research on the ability of the solute to form or break structures in water solvents. A statistical method called the ANOVA technique has been employed to qualitatively analyse the obtained results. A food preservative known as potassium metabisulphite preserves the natural colour of food. In beverages such as wine, juice, and beer, it acts as a bleaching agent. Besides protecting against bacteria, it also sanitizes fermenting vessels and wine bottles. Tap water can sometimes be disinfected using it in order to remove chloramines. A living being is dependent on water to survive and plays a vital role within the environment. So, it becomes extremely relevant to investigate the physio-chemical behaviour of potassium metabisulphite salts in water.
Enhancing Lower Limb Activity Recognition Through Multi-Sensor Data Fusion in Tele-Rehabilitation
Authors: Ettefagh Alireza , Fekr Atena Roshan 
Published: September 2023

Abstract
Background: Tele-rehabilitation is the provision of physiotherapy services to individuals in their own homes. Activity recognition plays a crucial role in the realm of automatic tele-rehabilitation. By assessing patient movements, identifying exercises, and providing feedback, these platforms can offer insightful information to clinicians, thereby facilitating an improved plan of care. This study introduces a novel deep learning approach aimed at identifying lower-limb rehabilitation exercises. This is achieved through the integration of depth data and pressure heatmaps. We hypothesized that combining pressure heatmaps and depth data could improve the model’s overall performance.
Methods: In this study, depth videos and body pressure data from an accessible online dataset were used. This dataset comprises data from 30 healthy individuals performing 7 lower-limb rehabilitation exercises. To accomplish the classification task, three deep learning models were developed, all based on a 3D-CNN architecture. The models were designed to classify the depth videos, sequences of pressure data frames, and combination of depth videos and pressure frames. The models’ performance was assessed through leave-one-subject-out and leavemultiple- subjects-out cross-validation methods. Performance metrics, including accuracy, precision, recall, and F1-score, were reported for each model.
Results: Our findings indicated that the model trained on the fusion of depth and pressure data showed the highest and most stable performance when compared with models using individual modality inputs. This model could effectively identify the exercises with an accuracy of 95.71%, precision of 95.83%, recall of 95.71%, and an F1-score of 95.74%.
Conclusion: Our results highlight the impact of data fusion for accurately classifying lower-limb rehabilitation exercises.We showed that our model could capture different aspects of exercise movements using the visual and weight distribution data from the depth camera and pressure mat, respectively. This integration of data provides a better representation of exercise patterns, leading to higher classification performance. Notably, our results indicate the potential application of this model in automatic tele-rehabilitation platforms.
Cost analysis of the management of end-stage renal disease patients in Abuja, Nigeria
Authors: Agada-Amade Yakubu Adole , Ogbuabor Daniel Chukwuemeka , Eborieme Ejimai , Onwujekwe Obinna Emmanuel 
Published: September 2023

Abstract
Background
Although the treatment for end-stage renal disease (ESRD) under Nigeria’s National Health Insurance Authority is haemodialysis (HD), the cost of managing ESRD is understudied in Nigeria. Therefore, this study estimated the provider and patient direct costs of haemodialysis and managing ESRD in Abuja, Nigeria.
Method
The study was a cross-sectional survey from both healthcare provider and consumer perspectives. We collected data from public and private tertiary hospitals (n = 6) and ESRD patients (n = 230) receiving haemodialysis in the selected hospitals. We estimated the direct providers' costs using fixed and variable costs. Patients' direct costs included drugs, laboratory services, transportation, feeding, and comorbidities. Additionally, data on the sociodemographic and clinical characteristics of patients were collected. The costs were summarized in descriptive statistics using means and percentages. A generalized linear model (gamma with log link) was used to predict the patient characteristics associated with patients’ cost of haemodialysis.
Results
The mean direct cost of haemodialysis was $152.20 per session (providers: $123.69; and patients: $28.51) and $23,742.96 annually (providers: $19,295.64; and patients: $4,447.32). Additionally, patients spent an average of $2,968.23 managing comorbidities. The drivers of providers’ haemodialysis costs were personnel and supplies. Residing in other towns (HD:β = 0.55, ρ = 0.001; ESRD:β = 0.59, ρ = 0.004), lacking health insurance (HD:β = 0.24, ρ = 0.038), attending private health facility (HD:β = 0.46, ρ < 0.001; ESRD: β = 0.75, ρ < 0.001), and greater than six haemodialysis sessions per month (HD:β = 0.79, ρ < 0.001; ESRD: β = 0.99, ρ < 0.001) significantly increased the patient’s out-of-pocket spending on haemodialysis and ESRD.
Conclusion
The costs of haemodialysis and managing ESRD patients are high. Providing public subsidies for dialysis and expanding social health insurance coverage for ESRD patients might reduce the costs.