bluuebunny/crossref_metadata_2025 huggingface dataset:
A Geographically Weighted Regression analysis of the underlying factors of Urban Heat Island phenomenon in Ghaziabad district of Uttar Pradesh
Authors: . Diksha , Kumari Maya , Rai Praveen Kumar , Kumar Deepak
Published: October 2023

Urbanization is important for societal development. However, it is accompanied by environmental concerns, such as a rise in the temperature of the local area in comparison to that of its surroundings; this phenomenon is known as an Urban Heat Island (UHI). The purpose of this study is to model UHI in the Ghaziabad district using Temperature of the Land's Surface (LST) for the Years 2011 and 2012, estimated from Landsat 7 and 8 respectively, using ArcGIS and SAGA GIS software. The results show that the mean LST increased by 3.11°C over the course of a decade. The Urban Thermal Field Variance Index (UTFVI) was used to map and characterise regions that had high UHI intensities. The areas with high UHI intensity were typically residential areas whereas the low intensity was found associated with cropland. In the Ordinary Least Squares Regression (OLS) regression model, Surface Albedo (SA), Sky View Factor (SVF), Solar Radiation (SR), and Normalized Difference Vegetation Index (NDVI) accounted for 58% of LST variability in 2011 and 66% in 2021. Because LST is nonstationary, a Geographically Weighted Regression (GWR), was utilised to demonstrate that the residuals are normally and randomly distributed.
Occlusal and masticatory aspects after application of Hall technique and conventional SSC – an 8 weeks comparative cohort study
Authors: He Pengcheng , Li Yiting , Wang Siwei , Zhou Xin , Zhou Yuan , Zheng Liwei
Published: October 2023

Objectives
By comparing the differences between Hall technique and traditional preformed mental crowns(PMC) in the treatment of extensive caries, this paper aims to investigate the treatment efficacy of Hall technique.
Materials and Methods
①Chlidren who needed metal crown restoration due to caries of mandibular deciduous molars, were selected. Oral dates were measured and analyzed in pre-op, post-op,2wk post-op, 4wk post-op and 8wk post-op.②Rebuild and compare the treatment modules through three-dimensional finite element analysis.
Results
①There were 21 (12males and 9 females) in the Hall technique group and 22(15 males and 7 females) in the traditional PMC group. All data with Hall technique changed immediately after operation, and returned to the preoperative level at 2wk post-op and 4wk post-op (P > 0.05). ②In treatment modules, the maximum stress value of Hall technique module increased immediately, and returned to the preoperative level.
Conclusion
After the Hall technique treatment, the occlusal state will gradually return to the preoperative state in about 2–4 weeks. The occlusal and masticatory prognosis is not significantly different from that of the traditional PMC technique.
Clinical Relevance:
This investigation demonstrates Hall technique’s safety in periodontitis and temporomandibular joint and effectiveness stopping caries developing.
Registration number: ChiCTR2100046097
Effective, versatile and inexpensive extruder system for direct ink writing of high-viscosity pastes
Authors: Rodríguez-Lagar Pablo , Reguera-García Alejandro , Llamas-Unzueta Raúl , Blanco Clara , Santamaría Ricardo , Montes-Morán Miguel A. , Menéndez J. Angel , Rocha Victoria G.
Published: October 2023

We offer the possibility of implementing a lab made extruder for direct ink writing (DIW) into a conventional fused deposition modelling (FDM) 3D printer. The ink extruder was designed to comply with various requirements including the possibility of using multiple syringe volumes, ease of assembly, compatibility with numerous commercial FDM printers, ink retraction and ink flow control, and the ability to extrude inks with a wide range of viscosities (ink yield stresses from 135–1100 Pa). The load in the extruder was attained by combining a stepper motor and a gear reduction system. The reduction system was connected to a trapezoidal threaded spindle through a rigid coupler. The movement of the spindle was transmitted to the plunger of a syringe that contained the ink (with volumes ranging from 3–30 mL), by means of a linear guide system. Most of the extruder parts were printed with the same FDM printer to which the DIW extruder ended attached to. The DIW extruder wiring connections were simply made by using the E-axis connectors available in the FDM printer. Modifications of the FDM printer software required for the correct control of the DIW extruder were also relatively simple, avoiding firmware modification. This simplicity made the two DIW and FDM heads easily interchangeable, thus amplifying the functionality of a conventional FDM printer. The cost of this new DIW extruder is approx. 100€.
Pelvic girdle pain in pregnancy and early postpartum – prevalence and risk factors in a multiethnic cohort
Authors: Robinson Hilde Stendal , Vøllestad Nina K , Bennetter Karin Elisabeth , Waage Christine Wiegels , Jenum Anne Karen , Richardsen Kåre Rønn
Published: October 2023

Background. Pelvic girdle pain (PGP) is common during and after pregnancy. It has been assumed that Scandinavian women report more PGP than women of other ethnicities. However, there are few population-based studies on ethnic differences and few with ethnicity as risk factor for PGP. The purposes of the present study were: To examine the prevalence of self-reported PGP through pregnancy and early postpartum in a multiethnic cohort. To investigate how ethnicity and patient characteristics were associated with risk of PGP during pregnancy and early postpartum. To investigate if clinical and personal factors obtained in gestation week 15 were associated with PGP in gestation week 28 and postpartum week 14.
Methods. This study analyzed questionnaire data from 823 women from the Stork- Groruddalen multiethnic cohort study in Norway. Chi-square tests were used to investigate ethnic differences in prevalence of self-reported PGP, and logistic regression analyses to identify factors associated with self-reported PGP.
Results. Women from South-Asia and Middle East reported 10-20% higher prevalence of self-reported PGP at all time points compared with Western women. Ethnicity was associated with PGP in gestation week 15 and postpartum week 14, adjusted for parity. Pain locations in pelvic area (PGP locations) in gestation week 15, especially combined symphysis and posterior pelvic girdle pain, gave the highest risk (OR=7.4) for PGP in gestation week 28 and in postpartum week 14(OR = 3.9). Being multiparous was a risk for PGP in postpartum week 14 (OR=1.9).
Conclusions. Women of South Asian and Middle Eastern background had higher risk of self-reported PGP than Western women. Ethnicity was associated with PGP in gestation week 15 and postpartum week 14, after adjustments for parity. PGP locations in gestation week 15 was the most prominent risk factor for PGP in gestation week 28 and postpartum week 14, whilst ethnicity was not significant in multivariable analyses.
Affiliate stigma and caring burden among primary caregivers of adult patients with severe mental illness: a facility-based cross-sectional study
Authors: Handebo Frehiwot , Kassim Faiz Mohammed , Alemayehu Selamawit , Amare Hermon
Published: October 2023

Introduction: Although caregivers play an important role in the treatment and recovery of various patients, several studies showed that primary caregivers of adults with severe mental illness (AWSMI) experience widespread stigma and have a high burden. However, there are limited studies in developing countries that assessed stigma and burden among primary caregivers of AWSMI.
Objectives: The present study aimed to assess affiliate stigma and caring burden among caregivers of AWSMI at St. Paul’s Hospital Millennium Medical College(SPHMMC), Addis Ababa, Ethiopia.
Methods: A facility-based cross-sectional study design was applied. A total of 375 caregivers of AWSMI were recruited using a systematic random sampling technique. Data were collected usinga systematic random sampling method. The collected data includes tools and structured questionnaires including the family stigma scale, attitude toward mental illness questionnaire, family burden interview, Oslo 3-items social support scale, sociodemographic and clinical characteristics of the caregivers and the patients, and burden of caregivers. Descriptive and binary logistic regression were performed to analyze the data.
Results: Caregivers (n =375) of patients with bipolar disorder (n = 50), anxiety disorders (n= 82), MDDs (n =103) and schizophrenia (n = 140) participated in the study, with a response rate of 95.7%. Half of the participants (187) were female. The results showed that around half (54.9%) of the caregivers experienced or perceived stigma. The factors that were associated with stigma among caregivers were caregiving patients with schizophrenia (AOR: 1.91; 95% CI: 0.86, 4.2; p = 0.003), attitude towards people with mental illness (AOR: 2.1; 95% CI: 1.23, 3.4; p = 0.005), social support (AOR: 0.5; 95% CI: 0.30, 0.82; p = 0.006), patient history of psychiatric admission (AOR: 0.32; 95% CI: 0.18, 0.57; p < 0.0001) and superstitious belief (AOR: 0.28; 95% CI: 0.15, 0.52; p < 0.0001). The findings also illustrated that a large proportion of caregivers (89%) had moderate to severe burden.
Conclusions: Overall, the current findings showed that stigma and burden among caregivers of AWSMI are high, indicating the urgent need to provide interventions such as psycho-education and contextualized support for caregivers and improving public’s awareness about mental illness. Furthermore, types of illness, social support, attitude towards people with mental illness, patient history of psychiatric admission and superstitious beliefs are important determinants of stigma.
Research on Community Perception Based on Street View Data Scoring Strategy
Authors: Pan Lu , Wan Yunshan , Xu Xiansheng , Li Qingyun
Published: October 2023

People are the main users of community street space. How to quantify street space quality from the perspective of people's perception and explore the relationship between street space quality and street elements has been a topic devoted to research in various fields. The development of big data and computer science provides a new technique for quantitative evaluation of street perception. The downtown area of Haikou city was taken as the research object to verify the method of this study. Street images of this area were used to construct a deep learning scoring model, and six dimensions of beauty, rich, safety, energetic, repression and [1] boredom were used to score perceptions. The six dimensions of perception are further divided into positive perception and negative perception. The top 20% of streetscape with the highest positive perception score was regarded as high-quality street space, while the top 20% of streetscape with the highest negative perception score was regarded as low-quality street space. The results showed that the highly urbanized area (Longhua district) was considered to be safer and more energetic, but at the same time, with higher sense of depression, there were significant differences incommunity perception among different types of POI, and community green space could significantly relieve the perception of depression. Therefore, this paper confirms the key role of urban functions in promoting sustainable urban development from the perspective of subjective perception, and provides scientific support for planning policies in terms of infrastructure service supply. By exploring the correlation between urban perception and urban functional pattern, this study finds that there is a strong nonlinear relationship between urban perception and urban functional structure. The case study quantitatively determines the impact of urban functions on city perception and illustrates the effectiveness of the proposed deep learning scoring method in promoting city perception evaluation.
The Invasion of Ukraine Viewed through TikTok: A Dataset
Authors: Steel Benjamin , Parker Sara , Ruths Derek
Published: October 2023

We present a dataset of video descriptions, comments, and user statistics, from the social media platform TikTok, centred around the invasion of Ukraine in 2022, an event that launched TikTok into the geopolitical arena. User activity on the platform around the invasion exposed myriad political behaviours and dynamics previously unexplored on this platform. To this end, we provide a mass-scale language and interaction dataset for further research into these processes. In this paper we conduct an initial investigation of language and social interaction dynamics, alongside an evaluation of bot detection on the platform. We have open-sourced the dataset and the library used to collect it to the public.
γ-polyglutamic Acid Application to Grassland on Sandy Soil: the Effect on Soil and Plant Functional Traits in Relation to Drought Stress
Authors: Skalski Tomasz , Zając Ewelina , Jędrszczyk Elżbieta , Papaj Katarzyna , Kohyt Joanna , Góra Artur , Kasprzycka Anna , Shytum Divine , Skowera Barbara , Ziernicka-Wojtaszek Agnieszka
Published: October 2023

The current study provides field experimental data that support the use of γ-polyglutamic acid (γ-PGA) in drought stress and proposes its application in grassland management. We hypothesized that water treatment combined with PGA application to sandy soil would reduce drought stress in grasslands more effectively than watering alone. A randomized block design was used, with three replicate watering blocks (no watering, weekly watering, and monthly watering) and PGA treatments at four different concentrations (0%, 0.3%, 1%, and 2% PGA). The results showed that PGA acts as a biostimulant, alleviating the effects of stress in plants by: 1) increasing the availability of ions, especially K+, Zn2+, Mn2+, Fe2+/3+, Ca2+, and Mg2+, as well as N-NH4+, and N-NO3−, 2) elongating plant roots, 3) increasing the aboveground biomass, 4) improving the resprouting capacity of the dominant grass Nardus stricta, and 5) improving the regeneration of dicotyledons. In the case of meadows on sandy soils, the use of low PGA concentrations (0.3% or 1%) was the most beneficial for the availability of macro- and microelements and improving the functional traits of plants. Irrigation had a greater effect than using PGA only for the dicotyledon to monocotyledon ratio.
Analysis of Cell-Free DNA to Predict Outcome to Bevacizumab Combination Therapy in Metastatic Colorectal Cancer Patients
Authors: Byrne Annette , Venken Tom , Miller Ian , Arijs Ingrid , Thomas Valentina , Barat Ana , Betge Johannes , Zhan Tianzuo , Gaiser Timo , Ebert Matthias , O'Farrell Alice , Prehn Jochen , Klinger Rut , O'Connor Darran , Moulton Brian , Murphy Verena , McDermott Ray , Bird Brian , Leonard Gregory , Grogan Liam , Horgan Anne , Schulte Nadine , Moehler Markus , Lambrechts Diether
Published: October 2023

To predict outcome to combination bevacizumab (BVZ) therapy, we employed cell-free DNA (cfDNA) to determine chromosomal instability (CIN), nucleosome footprints (NF) and methylation profiles in metastatic colorectal cancer (mCRC) patients.
Low-coverage whole-genome sequencing (LC-WGS) was performed on matched tumor and plasma samples, collected from 74 mCRC patients from the AC-ANGIOPREDICT Phase II trial (NCT01822444), and analysed for CIN and NFs. A validation cohort of plasma samples from the University Medical Center Mannheim (UMM) was similarly profiled. 61 AC-ANGIOPREDICT plasma samples collected before and following BVZ treatment were selected for targeted methylation sequencing.
Using cfDNA CIN profiles, AC-ANGIOPREDICT samples were subtyped with 92.3% accuracy into low and high CIN clusters, with good concordance observed between matched plasma and tumor. Improved survival was observed in CIN-high patients. Plasma-based CIN clustering was validated in the UMM cohort. Methylation profiling identified differences in CIN-low vs. CIN high (AUC = 0·87). Moreover, significant methylation score decreases following BVZ was associated with improved outcome (p = 0·013).
Analysis of CIN, NFs and methylation profiles from cfDNA in plasma samples facilitates stratification into CIN clusters which inform patient response to treatment
Stock market prediction using the LSTM algorithm in association with the Relative Strength Index (RSI) and Exponential Moving Average (EMA) indicators.
Authors: Dhokane Rahul Maruti , Agarwal Sohit
Published: October 2023

Because of the unpredictable nature of the financial market, stock prediction is very difficult. To invest investors' hard-earned money in the financial market, we require additional information. Traditional models like linear regression and Support Vector Regression (SVR) are used to predict stock prices, but they do not have much accuracy. Recurrent Neural Network (RNN) is having "vanishing gradient" issues. In this study, we explain the technique of combining the Long Short-Term Memory (LSTM) machine learning algorithm with leading indicators like the Relative Strength Index (RSI) and the Exponential Moving Average (EMA), i.e., the slow EMA, medium EMA, and fast EMA. For this study, we have selected seven different stocks from the National Stock Exchange (NSE), and the dataset period is from January 1, 2012, to December 31, 2022. When we add extra features like RSI, 50-day EMA, 100-day EMA, and 150-day EMA to traditional ones like open, high, low, close, and volume, we get better results than when we only use traditional ones like open, high, low, close, and volume. When the indicators are added along with the traditional features, the Mean Absolute Percentage Error (MAPE) goes down, the R2 score (coefficient of determination) goes up, and the model does better than the conventional model. This study and analysis helps to improve intraday trading by predicting the value and trend of certain stocks.
Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group in the Pediatric Population
Authors: Boerwinkle Varina L. , Appavu Brian , Cediel Emilio Garzon , Erklaurer Jennifer , Ganesan Saptharishi Lalgudi Lalgudi , Gibbons Christie , Hahn Cecil , LaRovere Kerri L. , Moberg Dick , Natarajan Girija , Molteni Erika , Reuther William R. , Slomine Beth S.
Published: October 2023

Background
The fundamental gap obstructing forward progress of evidenced based care in pediatric and neonatal disorders of consciousness (DoC) is the lack of defining consensus-based terminology to perform comparative research. This lack of shared nomenclature in pediatric DoC stems from the inherently recursive dilemma of the inability to reliably measure consciousness in the very young. However, recent advancements in validated clinical exams and technologically sophisticated biomarkers of brain activity linked to future abilities are unlocking this previously formidable challenge to understanding the DoC in the developing brain.
Methods
To address this need, the first of its kind international convergence of an interdisciplinary team of pediatric DoC experts was organized by the Neurocritical Care Society’s Curing Coma® Campaign. The multidisciplinary panel of pediatric DoC experts proposed pediatric-tailored common data elements (CDEs) covering each of the CDE working groups including behavioral phenotyping, biospecimens, electrophysiology, family and goals of care, neuroimaging, outcome and endpoints, physiology and big Data, therapies, and pediatrics.
Results
We report the working groups’ pediatric-focused DoC CDE recommendations and disseminate CDE to be used in studies of pediatric patients with DoC.
Conclusions
The CDE recommended support the vision of progressing collaborative and successful internationally collaborative pediatric coma research.
Evaluation of CNN Models Using Deep Reinforcement Learning for Band Selection on Hyperspectral Image Classification
Authors: Atik Saziye Ozge
Published: October 2023

Along with the high spectral rich information it provides, one of the difficulties in processing a hyperspectral image is the need for expert knowledge and high-spec hardware to process very high-dimensional data. The use of the most relevant bands in the hyperspectral image is quite decisive in deep CNN networks without loss of information and loss of accuracy. It is crucial to classify hyperspectral images with faster and less hardware-requiring models by creating subset groups by choosing a limited number of optimal bands. In this study, a comparative analysis about the effect of deep reinforcement learning (DRL)-based hyperspectral band selection on the classification performance of deep learning networks is presented. 3D CNN, 3D + 1D CNN and Multiscale 3D deep convolutional neural network (M3D-DCNN) algorithms were used for hyperspectral image classification. By choosing the most effective bands determined by DRL, it is aimed to perform classification with high accuracy with fewer bands instead of all bands. All tests were performed on popular hyperspectral datasets, Indian Pines, Salinas, and Pavia Center. The 3D + 1D approach reached 92.28% OA in the IP dataset. In Salinas, 94.87% OA with 3D CNN and 94.62% OA with M3D-DCNN was obtained. 3D + 1D CNN has 98.64% OA in PaviaC.
Semantic-wise hybrid attention generative adversarial network for image inpainting
Authors: Shi Changhong , Liu Weirong , Meng Jiahao , Li Zhijun , Liu Jie
Published: October 2023

Deep learning based image inpainting methods can synthesize plausible results based on known information of undamaged areas of the input image. However, most of the existing methods fail to generate high quality structures and textures due to a lack of fully exploring the potential high level semantic information of the generator. To address this issue, we first propose a novel Semantic-Wise Hybrid Attention Generative Adversarial Network (SWHA-GAN), which leverages a lightweight single-stream GAN framework to reconstruct reasonable and natural results. Secondly, a Semantic-Wise Hybrid Attention module is designed to simultaneously promote correct structure and rich details of the generated result. The channel self-attention emphasizes long range semantic dependencies among channels to improve structure accuracy, and spatial attention ensures texture inpainting. Experiments on multiple datasets including faces and natural images show that the proposed SWHA-GAN can generate higher quality results with more details than the state-of-the-arts.
Immunology of severe febrile illness in children in the COVID-19 era
Authors: Shankar-Hari Manu , Patel Harsita , Carter Michael , Jackson Heather , Powell Oliver , Fish Matthew , Barberio Manuela Terranova , Spada Filomena , Petrov Nedyalko , Wellman Paul , Darnell Sara , Mustafa Sobia , Todd Katrina , Bishop Cynthia , Cohen Jonathan , Kenny Julia , Berg Sarah van den , Sun Thomas , Davis Francesca , Jennings Aislinn , Timms Emma , Thomas Jessica , Nyirendra Maggie , Nichols Samuel , Elorrieta Leire Estramiana , D'Souza Giselle , Wright Victoria , De Tisham , Habgood-Coote Dominic , Ramnarayan Padmanabhan , Tissières Pierre , Whittaker Liz , Herberg Jethro , Cunnington Aubrey , Kaforou Myrsini , Ellis Richard , Malim Michael , Tibby Shane , Levin Michael
Published: October 2023

Severe febrile illnesses in children, such as multi-system inflammatory syndrome in children (MIS-C), severe bacterial infection (SBI), severe viral infection (SVI), and Kawasaki disease (KD), have shared clinical features. We used immunophenotyping with mass cytometry and cell stimulation experiments to illustrate shared and distinct mechanisms of immune dysfunction in 74 children with MIS-C, 30 with SBI, 16 with SVI, 8 with KD, and 42 controls. We then used targeted gene expression analysis to explore these findings in a secondary cohort of 500 children with these illnesses and 134 controls. Immunophenotyping and clustering analysis revealed neutrophil activation and apoptosis and T cell activation to be prominent in MIS-C and SBI. Cell stimulation experiments showed T cells from patients with acute MIS-C were exhausted. SVI was characterized by phosphorylated STAT signaling but lower gene expression for interferon receptors. Improved understanding of immune dysfunction may improve immunomodulator therapy in severe childhood febrile illnesses.
EIF4A3-mediated biogenesis of circSTX6 promotes bladder cancer metastasis and cisplatin resistance
Authors: Wei Wenjie , Liu Kan , Huang Xing , Tian Shuo , Wang Hanfeng , Zhang Chi , Ye Jiali , Dong Yuhao , An Ziyan , Ma Xin , Wang Baojun , Huang Yan , Zhang Xu
Published: October 2023

Background
Cisplatin (CDDP)-based chemotherapy is a standard first-line treatment for metastatic bladder cancer (BCa) patients, and chemoresistance remains a major challenge in clinical practice. Circular RNAs (circRNAs) have emerged as essential regulators in carcinogenesis and cancer progression. However, the role of circRNAs in mediating CDDP chemosensitivity has yet to be well elucidated in BCa.
Methods
CircSTX6 (hsa_circ_0007905) was identified by mining the public circRNA datasets and verified by Sanger sequencing, agarose gel electrophoresis, RNase R treatment and qRT-PCR assays. Then, function experiments were performed to evaluate the effects of circSTX6 on BCa metastasis. Luciferase reporter assay, RNA pull-down, RNA immunoprecipitation (RIP), RNA stability assay, fluorescence in situ hybridization (FISH) and immunofluorescence (IF) were conducted to evaluate the interaction among circSTX6, miR-515-3p, PABPC1 and SUZ12. Animal experiments were performed to explore the function of circSTX6 in tumor metastasis and CDDP sensitivity.
Results
We identified that circSTX6 was significantly upregulated in clinical samples and cells of BCa. Functionally, circSTX6 promoted cell migration and invasion both in vitro and in vivo. Mechanistically, circSTX6 could act as a miR-515-3p sponge and abolish its effect on SUZ12. Moreover, circSTX6 was confirmed to increase the stability of SUZ12 mRNA by interacting with a mRNA stabilizer PABPC1 and subsequently promote the expression of SUZ12. Importantly, silencing of circSTX6 improved the chemosensitivity of cisplatin-resistant bladder cancer cells to cisplatin. Furthermore, in vivo analysis supported that knockdown of circSTX6 attenuated the CDDP resistance in BCa tumors.
Conclusion
These studies demonstrate that circSTX6 plays a pivotal role in BCa metastasis and chemoresistance, and has potential to serve as a therapeutic target for treatment of BCa.
Empirical wavelet transform and wavelet mode decomposition for frequency characteristic extraction of EEG during sevoflurane general anesthesia
Authors: Yamochi Shoko , Yamada Tomomi , Obata Yurie , Sudo Kazuki , Kinoshita Mao , Akiyama Koichi , Sawa Teiji
Published: October 2023

Purpose
Mode decomposition methods are used to extract the characteristic intrinsic mode function (IMF) from various multidimensional time-series signals. Here, we applied wavelet transform-based mode decomposition to analysis of an electroencephalogram (EEG) recorded during general anesthesia.
Methods
An empirical wavelet transform (EWT) algorithm and a wavelet mode decomposition (WMD) algorithm with fixed frequency boundaries were added to previously reported EEG Mode Decompositor application software. Using our recently reported sevoflurane anesthesia data set, we performed EWT and WMD operations, and evaluated the significant characteristics via comparison with an existing variational mode decomposition (VMD) method.
Results
The EWT method, when decomposed into six IMFs, enabled narrowband separation of low-frequency bands IMF-1 to IMF-3, where all central frequencies were under 10 Hz. However, in the upper IMF of the high-frequency band with a center frequency ≥ 10 Hz, the dispersion of the frequency band covered was spread widely among the individual cases. In WMD, a narrow band of clinical interest can be specified using a band-pass filter via a Meyer wavelet filter bank within a specific mode decomposition discipline. When compared with VMD and EWT methods, the IMF decomposed using WMD is accommodated in a narrow band with a small variance for each case.
Conclusion
Although issues remain with the EWT, e.g., optimizing the process, the EWT can perform feature extraction similar to VMD. The Meyer filter bank used in the WMD represents an attractive technique for characteristic frequency band extraction when used as a band-pass filter in combination with the mode decomposition method.
Green tea is a protective factor that can preserve sperm DNA integrity: A retrospective study
Authors: Yang Wen , Geng Hao , Duan Zongliu , Gao Yang , shen Qunshan , Liu Liting , Wang Guanxiong , Zha Xiaomin , Xu Chuan , Zhou Ping , Wei Zhaolian , Song Bing , Tang Dongdong , Wu Huan , Li Guanjian , Cao Yunxia , He Xiaojin
Published: October 2023

Background: Although sperm DNA fragmentation index (DFI) is an vital biomarker for sperm DNA integrity and male fertility, factors that influence DFI have not been fully elucidated, particularly for occupational exposures and lifestyle factors. Here, we sought to explore the effects of self-reported occupational exposures and lifestyle factors on sperm DNA integrity.
Methods: The baseline characteristics, occupational exposures, and lifestyle factors of participants were collected immediately prior to or following semen evaluation through a self-report questionnaire. Participants were separated into three DFI-based groups: DFI<15%, 15%≤ DFI<30%, and 30%≤DFI. Initially, one-way ANOVAs and chi-square tests were employed to investigate the possible factors related to sperm DNA integrity. Then, we performed an ordered logistic regression analysis to detect factors independently associated with sperm DFI. To adjust for relevant confounders, we included factors with a P< 0.25 in univariate analyses as covariates.
Results: Among 1,060 subjects who participated in this study, 826 met the icludion cretieria. Univariate analysis showed that age, infertility type, infertility duration, semen parameters (concentration, motility and morphology) and smoking were related to sperm DNA integrity (P<0.05). At ordered logistic regression analysis, compared with the group that drank green tea 5-7 times/week, the groups that drank green tea <1 time/week (OR=1.52, 95% CI=1.05-2.2, and p=0.027) and 1-4 times/week (OR=1.61, 95% CI=1.02-2.54, and p=0.042) exhibited significantly increased sperm DFI values. Of the traditional semen parameters measured, a positive correlation was noted between sperm DFI and semen volume (OR=1.18, 95% CI=1.07-1.31) and abnormal sperm morphology (OR=1.2, 95% CI=1.11-1.3), whereas it was negatively correlated with sperm motility (OR=0.94, 95% CI=0.93-0.95). Relative to men over 40 years of age, we detected a 65% (95% CI=0.2-0.62) and 58% (95% CI=0.26-0.7) decrease in sperm DFI values in the 20-30 and 30-40 age groups, respectively.
Conclusions: These data suggest that green tea consumption is a protective factor associated with the preservation of sperm DNA integrity, which may offer new insights to guide the prevention and treatment of clinical male infertility.
Impact of an oral care subsidization reform on intersectional inequities in self-rated oral health in Sweden
Authors: Anticona Cynthia , Suominen Anna Liisa , Holgerson Pernilla Lif , Gustafsson Per E
Published: October 2023

Background
Oral health in Sweden is good at the population level, but seemingly with persisting or increasing inequities over the last decades. In 2008, a major Swedish reform introduced universal partial subsidies to promote preventive care and reduce the treatment cost for patients with extensive care needs. This study aimed to apply an intersectional approach to assess the impact of the 2008 subsidization reform on inequities in self-rated oral health among adults in Sweden over the period 2004–2018.
Methods
Data from 14 national surveys conducted over 2004–2018 were divided into three study periods: pre-reform (2004–2007), early post-reform (2008–2012) and late post-reform (2013–2018). The final study population was 118,650 individuals aged 24–84 years. Inequities in self-rated oral health were examined by intersectional analysis of individual heterogeneity and discriminatory accuracy across 48 intersectional strata defined by gender, age, educational level, income, and immigrant status.
Results
Overall, the prevalence of poor self-rated oral health decreased gradually after the reform. Gender-, education- and income-related inequities increased after the reform, but no discernable change was seen for age- or immigration-related inequities. The majority of intersectional strata experienced patterns of persistently or delayed increased inequities following the reform.
Conclusions
Increased inequities in self-rated oral health were found in most intersectional strata following the reform, despite the seemingly positive oral health trends at the population level. Applying an intersectional approach might be particularly relevant for welfare states with overall good oral health outcomes but unsuccessful efforts to reduce inequities.
Validation of a method based on liquid chromatography-tandem mass spectrometry for multiclass screening and analysis of 59 veterinary drugs in fishery foods
Authors: Park Sun-Young , Park Hyunjin , Kim Ji-Young , Choi Jang-Deok , Moon Gui-Im , Shin Dong Woo
Published: October 2023

Veterinary drugs (VDs) are regulated to prevent their abuse or misuse and protect humans that consume animal-based food products from exposure to VD residues. VD residues are managed according to the maximum residue limits (MRLs) or by prohibiting the use of VDs based on their residual properties and toxicities. However, all VD resides, even those that are not managed by MRLs, in animal-based food products will be regulated for public health improvement. Accordingly, herein, the applicability of an existing multiclass analytical method to the analysis of 59 VDs in fishery foods was validated. Applicability of this method to the analysis of VDs in livestock foods has already been confirmed. In this method, the sample was extracted with water:acetonitrile (1:4, v/v) followed by cooling, concentration, and analysis via liquid chromatography-mass spectrometry. Accuracies and precisions for three fishery foods (namely, flat fish, eel, and shrimp) were 63.7 − 120% and 1.9 − 30%, respectively, and a minimum of 63% (44/70) compounds could be quantified. This method is expected to improve the capabilities and efficiencies of monitoring VD residues in animal-based food products and will enhance food safety.
MAS-Net:A Novel Malaria Cell Detection Algorithm
Authors: Xiong Zhao , Wu Jiang
Published: October 2023

Malaria is one of the major global health threats. Microscopy examination is the ”gold standard” for malaria diagnosis designated by the World Health Organization. However, microscopy heavily relies on doctors’ expertise, leading to prolonged diagnosis times, reduced efficiency, and the risk of misdiagnosis. This paper introduces a multi-level attention split network (MAS-Net) that addresses the challenges of information loss in detecting small targets and the discrepancy between the detection head’s receptive field and target size. Additionally, we introduce a split contextual attention structure (SPCot) that incorporates contextual information and builds a novel feature extraction network around it. SPCot avoids excessive feature map channel compression, fully utilizes contextual information, reduces information loss, and improves detection performance. Furthermore, we propose the inclusion of a multi-scale receptive field detection head (MRFH) in the shallow detection layer. This module effectively adapts to targets of varying scales, enhances the receptive fields, and improves the detection performance of malaria cells. The model achieves a significant average accuracy of 75.9% on the publicly available malaria dataset.
Yer Tepki Analizlerinde Farklı Dinamik Kayma Modülü Yaklaşımları Kullanılarak Belirlenen Tepki Spektrumlarının Karşılaştırılması
Authors: NACAROĞLU Engin , YAĞCIOĞLU Berk , TOPRAK Selçuk
Published: October 2023

Deprem kaynaklı dinamik hareketlerin zemin içerisindeki dalga yayılımına bağlı olarak altyapı ve üstyapı sistemlerinde oluşturduğu etkilerin araştırılmasında kullanılan araçlardan biri tek boyutlu yer tepki analizleridir. Bu analizlerde zeminlerin dinamik özelliklerinin tanımlanmasında doğrudan çevrimsel yüklemeler ile gerçekleştirilen deneyler kullanılabilmektedir. Fakat bu deneylerin maliyetleri ve deney aletlerinin ulaşılabilirliğindeki zorluklar nedeniyle bu deneylerin yerine genellikle araştırmacılar tarafından geliştirilen modül azalım ve sönüm eğrileri kullanılmaktadır. Eğrilerin farklı veri setleri ve teknolojilere sahip deney aletleri ile hazırlanması, zeminin dinamik etkiler altındaki davranışlarında farklılıklara sebep olmaktadır. Literatürde bu farklılıkların giderilmesi konusunda çeşitli düzeltme parametreleri geliştirilmiştir. Fakat düzeltme parametrelerine rağmen eğrilerin birbiri ile tam uyumlu olduğundan bahsetmek mümkün değildir. Bu çalışmada dinamik davranış eğrileri ile elde edilen sonuçlar, bir vaka kapsamında incelenmiş ve değerlendirilmiştir. Dinamik eğrilerin yer tepki analizi ile elde edilen zemin davranış çıktılarına etkisi karşılaştırmalı olarak değerlendirilmiştir. Değerlendirmeler neticesinde yüzeye yakın killi zeminlerde dinamik kayma modülü etkilerinin uyumlu olduğu belirlenmiştir. Kumlu zeminler için ise tespit edilen uyumsuzluklar nedenleri ile birlikte açıklanmıştır.
Manta Vatozu Beslenme Optimizasyon Algoritması Kullanılarak Sismik Kırılma Verisinin Ters Çözümü
Authors: ÖZYALIN Şenol
Published: October 2023

Sismik kırılma yöntemi, mühendislik jeofiziği, mühendislik jeolojisi ve jeoteknik mühendisliği araştırma alanlarında kullanılan, özellikle mühendislik yapılarının inşasından önce zeminin özelliklerinin ortaya konmasında önemli bir role sahip olup etkili bir jeofizik yöntemdir. Bu çalışma, P dalgasının ilk varış zamanlarından P dalga hızının (Vp) 1B dağılımını tahmin etmek için yeni bir ters çözüm algoritmasının uygulamasını amaçlamaktadır. Tanıtılan ters çözüm algoritması, Manta Vatozu Beslenme Optimizasyonu (MVBO) algoritması, mühendislik problemlerin çözümü için geliştirilmiş olan biyolojik tabanlı sezgisel üstü alternatif bir optimizasyon yaklaşımıdır. Farklı optimizasyon problemlerini çözmek için manta vatozların hayatta kalabilmesi amacıyla sergiledikleri farklı yiyecek arama stratejilerinden ( zincir beslenme, siklon beslenme ve takla atarak beslenme) yararlanır. Bu çalışma, MVBO algoritmasının sismik kırılma yönteminde gözlenen ve hesaplanan varış zamanları arasındaki farkı en aza indiren 1B hız modelini bulmaya yönelik ilk örnektir. Sunulan yöntemin etkinlik değerlendirmesi için önce farklı çok tabakalı yapay sismik modellere uygulanmış ve daha sonra bu veri setine gürültü eklenerek yöntemin etkinliği irdelenmiştir. Son olarak, MVBO ters çözüm algoritması gerçek arazi verisine uygulanmıştır. İran'ın Doğu Azerbaycan eyaleti Malekan ilçesinde bulunan Leylanchay baraj sahasında toplanmış olan gerçek sismik kırılma veri kümesi kullanılmıştır. Hem yapay hem de arazi verisine ait model parametrelerinin kestirimi ve güvenilirliğinin belirlenmesi için, rölatif frekans dağılımları ve olasılık yoğunluk fonksiyonları (OYF) yardımıyla kestirim parametreleri istatistiksel olarak da test edilmiştir. Bulgular, çalışma alanının üç tabakadan oluştuğunu, ilk iki tabakanın alüvyon ve son tabakanın ana kayayı temsil ettiğini göstermektedir. Sonuçlar, sismik kırılma verilerinin yorumlanmasında MVBO ters çözüm algoritmasının uygun ve güvenilir sonuçlar verdiğini ortaya koymaktadır.
Performance Comparison of CNN Based Hybrid Systems Using UC Merced Land-Use Dataset
Authors: YAŞAR ÇIKLAÇANDIR Fatma , UTKU Semih
Published: October 2023

Remote sensing is the technology of collecting and examining data about the earth with special sensors. The data obtained are used in many application areas. The classification success of remote sensing images is closely related to the accuracy and reliability of the information to be used. For this reason, especially in recent studies, it is seen that Convolutional Neural Network (CNN), which has become popular in many fields, is used and high successes have been achieved. However, it is also an important need to obtain this information quickly. Therefore, in this study, it is aimed to get results as successful as CNN and in a shorter time than CNN. Hybrid systems in which features are extracted with CNN and then classification is performed with machine learning algorithms have been tested. The successes of binary combinations of two different CNN architectures (ResNet18, GoogLeNet) and four different classifiers (Support Vector Machine, K Nearest Neighbor, Decision Tree, Discriminant Analysis) have been compared with various metrics. GoogLeNet & Support Vector Machine (93.33%) is the method with the highest accuracy rate, while ResNet18 & Decision Tree (50.95%) is the method with the lowest accuracy rate.
Investigation of the Effects of Needle Designs on the Root Canal Irrigation Using Computational Fluid Dynamics
Authors: BULGU Selin , YILDIZELİ Alperen , ÇADIRCI Sertaç , YILDIRIM Sema
Published: October 2023

This study aims to investigate the effects of irrigation needles geometries on the flow inside the root canal and compare their irrigation performances based on Computational Fluid Dynamics (CFD) analyzes. CFD simulations of three commonly used close-ended irrigation needles were performed for various inlet Reynolds numbers and working lengths. Their irrigation performances were evaluated based on apical pressure and wall shear stress. The flow was assumed to be incompressible, turbulent and steady at all inlet Reynolds numbers. The closed-ended needles showed similar limited irrigant penetration toward the apex. Among all configurations, the Model C outperforms others as it provides the highest wall shear stress around the needle tip and the lowest apical pressures in the apical foramen, which reduces the risk of apical extrusion. The needle tip designs influence important parameters for the effectiveness and safety of the irrigation process.
Gestreifte Quelljungfer (Cordulegaster bidentata SELYS, 1843) im nördlichen Hunsrück: Erste Ergebnisse unter besonderer Berücksichtigung der Erfassungsmethodik (Odonata: Cordulegastridae)
Authors: Masius Patrick
Published: October 2023

Die Gestreifte Quelljungfer (Cordulegaster bidentata) wurde 2016, 2017 und 2018 im nördlichen Hunsrück kartiert. An zehn der zwölf untersuchten Quellen konnten Nachweise der Art erbracht werden. Bis zu der Untersuchung existierte nur ein mehrere Jahrzehnte alter Nachweis von C. bidentata aus dem Untersuchungsgebiet. Die Ergebnisse der vorliegenden Untersuchung untermauern die These, dass im nördlichen Hunsrück ein Verbreitungsschwerpunkt von C. bidentata in Rheinland-Pfalz liegt. Die Erfassungsprobleme beim Nachweis der Art wurden über eine Methodendiversifizierung (Larven-, Exuvien- und Imagineserfassung) berücksichtigt. Die Ergebnisse der verschiedenen Erfassungsmethoden werden im Einzelnen dargestellt und diskutiert. Insgesamt sprechen sie dafür, dass eine Kombination aller drei Erfassungsmethoden der herkömmlichen Larvenmethode überlegen ist.
Nahrungsökologie der Waldohreule (Strigidae: Asio otus) auf dem ehemaligen Truppenübungsplatz Schmidtenhöhe bei Koblenz
Authors: Achenbach Michelle , Dehling J. Maximilian
Published: October 2023

Die Zusammensetzung der Nahrung der Waldohreule auf dem ehemaligen Truppenübungsplatz Schmidtenhöhe bei Koblenz wurde über direkte Beobachtung und durch die Analyse von Gewölleinhalten untersucht. Die Nahrung bestand fast ausschließlich aus Nagetieren (Rodentia: Muridae, Cricetidae). Waldmäuse (Apodemus fl avicollis, A. sylvaticus) waren die häufigsten Beutetiere; die meist als wichtigstes Beutetier identifizierte Feldmaus (Microtus arvalis) machte einen vergleichsweise geringen Anteil der Beute aus. In zwei Gewöllen wurden Kirschkerne (Prunus sp.) gefunden.
Zur Identität des Sägeblättrigen Gänsefußes (Chenopodium rhombifolium WILLD., Chenopodiaceae) und seiner Verbreitung im südwestdeutschen Raum und im angrenzenden Lothringen
Authors: Wisskirchen Rolf , Weicherding Franz-Josef
Published: October 2023

Genauere Untersuchungen an einer Sippe, die bislang unter dem Namen Chenopodium urbicum var. intermedium bzw. Ch. rubrum var. intermedium bekannt war, ergaben, dass es sich um eine eigenständige Art handelt, die sehr wahrscheinlich aus der allotetraploiden Hybrid-Verbindung von Ch. rubrum mit Ch. urbicum entstanden ist. Die Geschichte ihrer Entdeckung ist facettenreich, z.B. im Hinblick darauf, dass die europäische Art zuerst aus der Neuen Welt beschrieben wurde. Als diagnostische Merkmale von Ch. rhombifolium können genannt werden: die sägeblattartige Blattzähnung, die von Ch. urbicum abweichende Blattnervatur, der blattunterseitige Blasenhaarbesatz und die langen, spreizenden Infloreszenzäste (bei Ch. urbicum rutenartig anliegend). Bei den Blütenmerkmalen fällt die gegenüber Ch. urbicum erhöhte Anzahl von 4-zählig reduzierten Blüten auf. Unter nomenklatorischen Aspekten wird für Ch. rhombifolium Willd. (1809) ein Epitypus bezeichnet und der synonyme Name Ch. intermedium MErt. & KOch (1826) lektotypisiert. Regionale Daten zur Verbreitung werden präsentiert, die im Rahmen von Feldstudien, ergänzt durch Herbar-, Foto- und Literaturauswertung, erhoben wurden. Die Nachweiskarte zeigt, dass die Art früher im südwestdeutschen Raum verbreitet war. Typische Standorte waren Miststellen mit Jaucheausfluß. Heute ist die Art in Deutschland selten geworden und fast nur noch in der nördlichen Oberrheinebene auf Sekundärstandorten (Deponien, Sandabgrabungen) zu finden. Weiter westlich in Frankreich ist der Sägeblättrige Gänsefuß im Bereich dörflicher Ruderalstellen dagegen noch verbreitet. Insgesamt zeigt sich ein westeuropäischer Schwerpunkt, während Ch. urbicum mehr kontinental und mediterran verbreitet ist. 12 Vegetationsaufnahmen mit Ch. rhombifolium werden vorgelegt.
Wirtsbindung von Cuscuta-Arten am Unteren Mittelrhein
Authors: Kosack Lutz , Möseler Bodo Maria
Published: October 2023

Die Gattung Cuscuta wurde an den Ufern des Unteren Mittelrheins kartiert. Die Taxon-spezifische Wirtspräferenz von Cuscuta gronovii, Cuscuta europaea und Cuscuta lupuliformis wurde untersucht. In diesem Zusammenhang wurden zahlreiche Vegetationsaufnahmen mit Vorkommen von Cuscuta-Arten analysiert. Zusätzlich wurden 500 Datensätze von Cuscuta insbesondere hinsichtlich ihres spezifischen Wirts untersucht. Die Vegetationsaufnahmen wurden mit dem COCKTAIL-Algorithmus im Softwarepaket JUICE und dem implementierten statistischen Treuemaß ‚u‘ analysiert. Diese Ergebnisse zeigen eine starke Bindung zwischen Cuscuta lupuliformis und Rubus caesius sowie zwischen Cuscuta gronovii und Solidago gigantea. Urtica dioica tritt als Wirt von höchster Bedeutung für Cuscuta europaea auf, aber die gegenseitige Bindung erscheint schwächer. Aufgrund ihrer biogeographischen Herkunft ist zu beachten, dass sowohl Cuscuta gronovii als auch Solidago gigantea eine „gewisse Affinität“ zueinander haben.