bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring coastal bathymetry retrieval for ocean modeling: a case study from West Africa
Authors: Marchesiello Patrick , THOUMYRE Grégoire , Dieye Arame , Almar Rafael , Erwin Bergsma , Sow Bamol Ali , Duong Thuan Hai
Published: April 2024

Coastal risk assessment requires accurate coastal bathymetry, which is largely lacking in many regions of the world's coastal oceans. This is particularly true in Guinea-Bissau, where the tidal range is the highest of any country in West Africa, affecting several socio-economic sectors such as agriculture and urban development. Here we present a selection of coastal bathymetry datasets available for generally poorly sampled coastal regions. These include the global GEBCO product, digital nautical charts (CMAP), and depth retrieval from satellite wave detection (S2Shores). While GEBCO provides the right regional envelop of bathymetry, the coastal zone is plagued with random bumpiness at scales below 10 km. S2Shores can be used to correct these errors and instead reveal the presence of small scale channels, reminiscent of very high-resolution satellite color images. These structures are also confirmed by nautical charts, which show the channels to be deeper than that indicated by the satellite retrieval. In simulations with the hydro-sedimentary coastal ocean model CROCO, the tidal energy flux is better channeled towards the coast in the CMAP and S2shores cases, while GEBCO produces larger form drag and sediment bed response, acting as a bathymetric correction to minimize friction. This result highlights the potential of combining different approaches to estimate up-to-date coastal bathymetry in the most challenging areas.
DilateTrans Tracker
Authors: xu dong , shao leijie
Published: April 2024

DilateTrans Tracker is a novel object tracking algorithm that seamlessly integrates the power of dilated attention and transformer architectures. Leveraging the strengths of both components, DilateTrans Tracker achieves robust and efficient tracking performance in complex scenarios. The dilated attention mechanism allows the model to capture long-range dependencies and spatial relationships among objects, while the transformer architecture enables effective feature extraction and global context modeling. The fusion of these two techniques results in a comprehensive solution for multi-object tracking that excels in handling diverse and dynamic scenarios. Extensive experiments demonstrate the superior performance of DilateTrans Tracker compared to state-of-the-art tracking methods, making it a promising choice for real-world applications requiring accurate and reliable object tracking.
A study of a seasonal influenza model in deterministic and stochastic environments
Authors: Zhang Xiaoshan , Zhang Xinhong , Jiang Daqing
Published: April 2024

Seasonal influenza occurs annually and is one of the most common infectious diseases in the world, posing a threat to public health security. Therefore, it is essential to study the dynamics of seasonal influenza to raise public awareness and implement scientific prevention measures. Huo et al. studied a deterministic seasonal influenza model in Gansu, China, in this paper, we extend their study starting from proving the local asymptotic stability of the endemic equilibrium. In addition, considering the non-negligible effects of environmental disturbance on the transmission of influenza viruses, we assume that the transmission rate in the deterministic model follows a log-normal Ornstein-Uhlenbeck process, therefore, we formulate the corresponding stochastic model. To analyze the dynamics of the stochastic model, we first verify the existence and uniqueness of the global positive solution. Next, by constructing suitable Lyapunov functions, we obtain sufficient conditions for the stationary distribution and the extinction of the disease. More precisely, we deduce that the seasonal influenza persist when R0s > 1 while it dies out when R0 E < 1. Furthermore, we derive the exact expression of probability density function around the quasi-endemic equilibrium. Finally, we conduct numerical simulations to validate theoretical results and further explore the effects of environmental noise.
RETRACTED: SIS-CAM: An Enhanced Integrated Score-Weighted Method Combined with Gradient Optimization for Interpreting Convolutional Neural Networks
Authors: Zhang Yuquan , Khan Umer Sadiq , Xu Fang , Zhang Yan , Li Zhimin , Ma Yi , Liu Zhen , Yang Na
Published: April 2024

The authors have requested that this preprint be removed from Research Square.
Empirical Relationship Between Shear Wave Velocity and Geotechnical Properties of Residual Soil
Authors: Jais Ismacahyadi Bagus Mohamed , Halim Muhammad Izzat Abdull , Lat Diana Che
Published: April 2024

Some locations or site studies do not have adequate geophysical and geotechnical data due to the cost and time constraint. A strong correlation between shear wave velocity (Vs), Standard Penetration Test (SPT-N) values and soil density could be an alternative method to estimate those parameters without additional investigation or data acquisition. This study investigates the empirical correlation among Vs, SPT-N values, and bulk density in the Bangsar region. The research employs an extensive dataset collected from Lorong Bukit Pantai 4, Bangsar and Jalan Bangsar, Bangsar. Vs measurements are obtained using Multichannel Analysis Surface Waves (MASW) Survey. SPT-N is extracted from geotechnical borehole records, and bulk density is determined through laboratory testing. Statistical analyses, including correlation coefficients and regression analysis, are applied to assess the relationships among Vs, SPT-N, and bulk density. Vs = 73.171N0.4365, and Vs = 42.985ρ3.4576 with a regression coefficient of R2 = 0.9863 and R2 = 0.888 is the "Power Model" from non-linear regression analysis that is used to generate the correlation. Numerous statistical techniques, such as Root Mean Square Error (RMSE) analysis and Graphical Residual Analysis, have been used to assess the accuracy of the proposed correlation. A strong correlation between Vs, SPT-N values and soil density could be an alternative method to estimate those parameters without additional investigation or data acquisition, result in time and cost savings by reducing the need for extensive and redundant testing.
Farmer Ants Optimization Algorithm: A new meta-heuristic for solving discrete optimization problems
Authors: Zeinalabedinmalekmian Mahdi , Asghari Ali , Azgomi Hossein , Alimoradi Mahmoud , Ghaziantafrishi Shirin
Published: April 2024

Today, some complex problems are known as NP-hard problems. For this category of problems, there is no exact solution or they are not solvable in a reasonable time. For this reason, metaheuristic algorithms have been introduced and developed. These algorithms attempt to find an optimal solution to the problem instead of finding a definite solution. In recent years, these algorithms have gained significant attention from researchers. The major inspiration for metaheuristic algorithms is nature and its laws. An important category of these algorithms is evolutionary algorithms. These algorithms are inspired by the behavior of animals and living organisms that exhibit social and intelligent behavior. However, each metaheuristic algorithm may optimally solve just some types of problems. Therefore, researchers continuously try to introduce new algorithms. In this study, a new metaheuristic algorithm called Farmer Ants Optimization Algorithm (FAOA) is introduced. This algorithm is based on the intelligent life of farmer ants. Farmer ants cultivate mushrooms to provide food for themselves. They also protect them against various pests, and after growth, feed them. These special behaviors of farmer ants, which are based on their social life, are the source of inspiration for the proposed method. Experiments on some engineering and classical problems have shown that FAOA can provide an acceptable solution for discrete optimization problems.
A Novel Approach to Image Steganography: A Fusion of Chaotic and Genetic Algorithms for Unbreakable Data Hiding
Authors: Thangaraju Dineshkumar , R Asokan
Published: April 2024

Image steganography comprises concealing sensitive data inside digital images to ensure secure communication. In this work, a ground-breaking method for image steganography is introduced, which fuses chaotic and genetic algorithms, aiming to create a strong and impenetrable data concealment technique. The study applies Integer Wavelet Transform (IWT) to the image and services logistic map chaotic system to produce pseudo-random sequences. These sequences take a significant in identifying the most secure positions within the image to embed confidential message bits. This embedding process is highly secure and resilient against statistical attacks. Moreover, a genetic algorithm optimizes this process, bolstering the security of the steganography approach. Using a population-based search technique, the genetic algorithm efficiently explores the search space, identifying the optimal chromosome representation for data embedding. This significantly enhances the embedding capacity while minimizing distortion to the original image. Through extensive experimental evaluations and performance analyses, the study showcases the effectiveness and resilience of this proposed approach. The findings highlight that combining chaotic and genetic algorithms in image steganography markedly improves security, capacity, and resistance to attacks when compared to traditional methods. This steganographic scheme achieved a PSNR of 55.3392 dB, a MSE of 0.3620, a SSIM of 0.9744, and a VIF of 0.9269. Additionally, the work demonstrated a hidden information capacity of 3.67 bits per pixel (BPP).
Facile synthesis of Samarium (Sm 3+ ) doped Cobalt-iron oxide nano ferrite as an advanced electrode material for supercapacitor applications
Authors: Khasim Syed , PASHA APSAR , BN Ramakrishna , B.S Prathibha , P.R Koushalya
Published: April 2024

Herein, we present the design and fabrication of samarium (Sm3+) doped cobalt-iron oxide ferrites nanocomposites for utilization as an efficient energy storage material. We have employed a simple, low cost and quick one step solution combustion method used to synthesize CoFe2 − xSmxO4 (x = 0.0, 0.050, 0.075 and 0.1) ferrites composites. The synthesized CoFe2 − xSmxO4 NPs undergo different analytical and spectroscopic characterizations methods like scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDS), transmission electron microscope (TEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and ultraviolet visible (UV-visible) analytical and spectroscopic methods that used to confirm the morphological and structural properties of the synthesized NPs. The electrochemical properties synthesized ferrites composites were significantly improved after inclusion of rare earth (RE) metal such as samaniuim (Sm3+) nanoparticles (NPs) into the host cobalt-iron-oxide. It was notice that the creation of single phase in pure CoFe2 − xSmxO4 ferrite remains unaltered by the mechanism of doping even in the ferrites composite. Nevertheless, doping of RE metal significantly influences over the morphological and structural properties, further more enhancement in the electrochemical performance of samarium doped CoFe2 − xSmxO4 ferrite composite. The highest specific capacity about 850 F/g was achieved for CoFe2 − xSmxO4 (x = 0.1) composite electrode material, which shows more superior in compare to pure CoFe2 − xSmxO4 (x = 0) which is about 340 F/g. However, CoFe2 − xSmxO4 (x = 0.1) composite shows a superior capacitance retention of the order of 98% even after 5000 cycles of operation at a scan rate of 250 mV/s. The electrode material fabricated by using CoFe2 − xSmxO4 ferrite composites behave as positive electrode and at the same time activated nickel behave as negative electrode which is render an energy density of 30.16 Wh/kg at a power density of 400 Wh/kg. The results obtained in presented studies offer a hopeful way for the fabrication high-performance electrode material for supercapacitor which is more suitable for light weight electronic devices, electric vehicles, and forthcoming generation supercapacitor applications.
Livestock farmer-reported knowledge and attitudes regarding agroforestry planning and management
Authors: De-Sousa Karolini Tenffen , Wright Melanie , Cárdenas Laura , Deniz Matheus , Dittrich João Ricardo , Hötzel Maria José , Enriquez-Hidalgo Daniel
Published: April 2024

This study aimed to explore the knowledge and attitudes of livestock farmers from the United Kingdom regarding agroforestry planning and management issues. The farmers (n = 48) answered an online survey with demographic, open, closed and Likert scale questions. Almost half of the participants said they need more information to successfully plan and manage an agroforestry, and self-reported low knowledge on management practices related to trees. Participants stated they did not expect getting technical support from governmental agencies to maintain the agroforestry area. However, they would like to improve their knowledge trough field days, courses, and Internet sources. Benefits to the environment, animals and farm profitability were considered central to successful agroforestry systems. In conclusion, participants cannot successfully plan and manage agroforestry, but they are willing to improve their knowledge and skills.
Identification of Groundwater recharge zone in peri urban watershed with the help of MAUT and MEREC techniques
Authors: Begam Sadria , Majumder Mrinmoy
Published: April 2024

A catchment area that is neither rural nor urbanised is referred to as a peri-urban watershed. These basins have unique hydrological and geophysical features that interact directly with the local water demand. In addition to becoming scarce in terms of useable surface water, ground water is gradually but steadily getting less in many parts of the world. As a consequence, many heavily urbanised metropolises are experiencing a severe water scarcity, while many rural areas are rapidly becoming desert due to unchecked resource extraction. The issue pertaining to peri-urban watersheds is distinct in that the population that depends on them is neither very huge nor small, resulting in a moderate water scarcity. Their interactions are becoming more and more significant as a result of the little urban colonies that are sprouting up in response to the fierce competition for the existing resources that is seen in metropolitan settings. As a result, many rural regions are being transformed into periurban areas. Now, in order to meet the water needs of the periurban population, it is crucial to determine the ground water recharge zone. However, because of the physical makeup of the watersheds, each element plays a more significant role in determining the probable ground water recharge zones. In order to anticipate the significance of each element and, with the aid of the results, identify the probable GWR zones, the current work attempts to utilize novel MCDM techniques like MAUT and MEREC. Previous research has attempted to detect GWR using MCDM and GIS approaches; however, the focus of these studies was not on periurban watersheds, but rather on micro, meso, or macro level basins. Furthermore, since the application of MEREC and MAUT for these objectives has never been tried, the current study is novel and can assist engineers and urban planners in developing plans for sustainable development that will guarantee that residents in periurban watersheds experience no water stress.
A case-control study based on the National Health and Nutrition Examination Survey to evaluate the effects of human papilloma virus on bone health in women
Authors: Li Xiang , Jiao Guangjun , Chen Yunzhen
Published: April 2024

Background
Human papillomavirus (HPV) infection and osteoporosis (OP) are global health concerns, with higher prevalence observed in women compared to men. However, the impact of HPV infection on bone health remains uncertain.
Methods
This case-control study utilized data from the National Health and Nutrition Examination Survey (NHANES). Comparable datasets were created using nearest neighbor propensity score matching (PSM) at a ratio of 1:1. The association between HPV infection and bone mineral density (BMD) was analyzed using the Welch two-sample t-test. Furthermore, linear mixed models were employed for validation purposes. Restricted cubic spline (RCS) analysis and Kendall's tau-b tests were performed to explore the effect of different types of HPV infection on BMD.
Results
Individuals with HPV infection had lower BMD in the lower limbs and lumbar spine compared to uninfected individuals. RCS analysis revealed that an increasing number of cooccurring HPV types in women was associated with lower BMD. Specifically, four HPV types were negatively associated with lower limb BMD, while 14 HPV types were negatively associated with lumbar spine BMD. Additionally, HPV types 53, 59, and 89 exhibited effects on both lower limb and lumbar spine BMD.
Conclusions
HPV infection is associated with a decrease in BMD, and co-infection with multiple types of HPV implies even lower BMD. Appropriately designed trials are needed to determine if interventions targeted at preventing HPV infection can have a protective effect on BMD.
Fast No-reference Deep Image Dehazing
Authors: Qin Hongyi , Belyaev Alexander
Published: April 2024

This paper presents a deep learning method for image dehazing and clarification.The main advantages of the method are high computational speed and usingupaired image data for training. The method adapts the Zero-DCE approach for the image dehazing problem and uses high-order curves to adjust the dynamicrange of images and achieve dehazing. Training thhe proposed dehazing neuralnetwork does not require paired hazy and clear datasets but instead utilizes a setof loss functions, assessing the quality of dehazed images to drive the trainingprocess. Experiments on a large number of real world hazy images demonstratethat our proposed network effectively removes haze while preserving details andenhancing brightness. Furthermore, on an affordable GPU-equipped laptop, theprocessing speed can reach more than 1000 FPS for images with 2K resolution,making it highly suitable for real-time dehazing applications.
Data analysis and Forecasting of Tuberculosis and HIV co-infection: Exploring models from classical statistics to machine learning
Authors: Abade Andre , Porto Lucas Faria , Scholze Alessandro Rolim , Kuntath Daniely , Barros Nathan da Silva , Berra Thaís Zamboni , Ramos Antonio Carlos Vieira , Arcêncio Ricardo Alexandre , Alves Josilene Dália
Published: April 2024

Considering the complexity and severity of TB/HIV coinfection, accuracy in forecasting future trends is crucial for the efficient allocation of public health resources and the development of intervention strategies. This study explores the application of predictive models, ranging from classical statistical approaches to machine learning techniques, to analyze the time series of TB/HIV coinfection case notifications stratified for men, women, and the general population. Traditional models using Exponential Smoothing and Autoregressive Integrated Moving Average (ARIMA) methods were initially applied, providing a basis for understanding the overall temporal trend and the presence of seasonality. Subsequently, machine learning models, including Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and Deep Neural Networks such as Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN), were tested to find the best model to capture the complex dynamics of TB/HIV coinfection and the inherent non-linearities in the data. Performance evaluation, based on error metrics such as MSE, MAE, and sMAPE, revealed that Deep Learning models, especially Bidirectional LSTM and CNN combined with LSTM, significantly outperformed the classical statistical methods, demonstrating the effectiveness of these techniques for modeling TB/HIV coinfection time series and, consequently, providing more accurate forecast models.
Association between prolactin and history of stress fracture in elite sprinters and jumpers
Authors: Tsukahara Yuka , Torii Suguru , Taniguchi Yukiko , Kusakabe Torao , Murakami Hideki , Yamasawa Fumihiro , Akama Takao
Published: April 2024

Purpose Research related to stress fractures and the female athlete triad is abundant. However, since there is not enough evidence to support the risk factors for stress fractures is not sufficient. The aim of this study is to investigate the risk factor for stress fractures and the characteristics of the laboratory data of them in eumenorrheic female track and field athletes competing at an elite levelMethods Eumenorrheic sprinters and jumpers competing at a national level were recruited. Bone mineral density, bone metabolism markers, 25-OH Vitamin D, and hormones including prolactin and free testosterone were measured.Results A total of 84 high school and collegiate athletes were enrolled in the study, and among them, 33 athletes had a history of stress fracture after high school. Their personal background, bone mineral density, bone metabolism markers, 25-OH Vitamin D, and free testosterone were not different between the group with a history of stress fracture and without a history of stress fracture. Prolactin was higher in those with stress fractures compared to those without stress fractures, and it was statistically different between the two groups (15.70 ± 10.59 ng/mL and 11.59 ± 5.06 ng/mL, respectively, p = 0.019). Logistic regression analysis revealed that it was also a significant predictive factor for stress fractures (odds ratio: 1.10; 95% CI: 1.01–1.20; P = 0.023).Conclusion Prolactin may be linked to stress fractures in eumenorrheic sprinters and jumpers.
Research on textile Defect detection Algorithm for Deep Learning
Authors: Si Yachao , Gao Jiajie , Zhao Xingxuan
Published: April 2024

Textile defect detection is a crucial aspect of the textile industry. However, the detection accuracy is often low due to the small size of textile defects and the influence of fabric texture background. To address these issues, we propose a textile defect detection algorithm based on YOLOv8.The reparameterized structure was introduced to the original YOLOv8 to achieve hardware efficiency with the RepGhost module. The head section incorporates a new GD Mechanism and includes the Wasserstein Distance loss function.This method accurately identifies the location and type of defects in textiles with high precision under complex backgrounds, meeting the needs of industrial textile production. We conducted training and comparison experiments on different models using the AITEX public dataset and Roboflow open source dataset. We also designed ablation experiments to verify the considerable improvement of each enhancement on the evaluation index. The experimental results indicate that the detection accuracy of the enhanced YOLOv8 model in the task of detecting textile defects has increased by 18.9\% to 93.8\% on the public dataset. The number of parameters has increased by 10.94MB, and the FLOPs have increased from 8.2G to 11.3G. The improved algorithm has significantly enhanced the accuracy. It can effectively handle large amounts of data and recognize defects even under complex backgrounds, meeting the fast, complex, and high-precision requirements of the textile industry.
Establishment and validation of a nomogram model for predicting failed conversion of epidural labor analgesia to epidural surgical anesthesia in parturients undergoing intrapartum cesarean delivery
Authors: LI Zhiyue , Xinlu Fu , Dan Lu
Published: April 2024

Objective
The emergency conversion of epidural labor analgesia to intrapartum cesarean section anesthesia can lead to serious maternal and neonatal complication. This study aimed to establish a clinical predictive model to identify the risk of failed epidural conversion (FEC).
Methods
Clinical characteristics of 286 parturients who underwent conversion from epidural labor analgesia (ELA) in the Clinical Medical College of Yangzhou University were retrospectively collected. Univariate analysis and multivariate logistic regression were used to identify FEC risk factors. Risk factors were used to develop a predictive nomogram model. Area under the receiver-operating characteristic curve (AUC) calibration plots, and decision curve analysis (DCA) were used to assess the performance of the nomogram model.
Results
Independent predictors for FEC risk included ELA duration, non-obstetric anesthesiologist, visual analogue scores (VAS) within 2 h preceding cesarean section and size of the cervical orifice. The clinical prediction model was established based on the above four risk factors and showed superior predictive power both in training cohort (AUC = 0.876) and validation cohort (AUC = 0.839). The nomogram was well-calibrated. The decision curve analysis displayed that the FEC risk nomogram was clinically applicable.
Conclusions
The nomogram model can be used as a reliable and simple predictive tool for the identification of FEC, which will provide practical information for individualized treatment decisions.
High Speed Steel tool performance through hybrid texturing followed by shock peening towards sustainable machining
Authors: Prasad K. Nagendra , Ismail Syed , Satish M
Published: April 2024

Surface texturing is a promising sustainable technique to get better the machining performance of cutting tools. Laser surface texturing and micro-EDM are the most commonly used fabrication techniques and the textured tools exhibit better tool performance as compared to conventional tool. However, these processes involve re-solidification of material surface which makes the surface softening and reduction in the surface hardness. In the present work, cutting performance of the High-Speed Steel (HSS) tool is studied by fabricating hybrid (micro-grooves with dimples) textures on its rake face using both laser ablation and micro-EDM methods followed by laser shock peening without ablative coating (LSPWAC) process. Hybrid textured with shock peened HSS tools are used in orthogonal dry turning of 316 L stainless steel. It has been observed that hybrid textures with shock peened HSS tool exhibits higher tool life of up to 255% and 85% than the conventional and the hybrid textured (HT) tools respectively. The results shown that surface texturing followed by shock peening is an innovative method to improve the sustainability in machining process than only surface texturing method. Moreover, analysis of chip is studied by finite element analysis.
Accuracy assessment of old large-scale maps and reducing positional error in land use change analyses
Authors: Kratochvílová Darina , Cajthaml Jiří
Published: April 2024

Context Old large-scale maps are one of the main data sources on historic landscapes and form the basis of many landscape studies. However, few studies have addressed the issue of assessing the accuracy of map sources and the impact of this accuracy on the results of spatiotemporal analyses of landscape evolution.Objectives The purpose of this study was to verify the positional accuracy of large-scale maps used in landscape analyses and to test the possibility of eliminating the influence of mutual positional inconsistency of map sources on the results of this analysis. Narrow residual polygons, referred to as sliver polygons, arising during overlay operations because of positional errors in old maps can affect the results of the analysis, so it is appropriate to determine to what extent this happens, whether and when it is necessary to eliminate their influence and by what methods.Methods The positional accuracy of the vector models derived from old maps was verified in three model areas around the Vltava River by quantifying the mean positional error of a set of control points. Different methods for removing sliver polygons were proposed and tested for the selected test area within the model area by comparing the selected results of the spatiotemporal analysis.Results The achieved values of the mean positional errors for the historical data models from the mid-19th and mid-20th centuries are in the range of three to four metres for the model areas, which is highly accurate considering the scale values of the old maps used, confirming the suitability of these maps for landscape studies. The reverse vectorization of the time series of the maps eliminated the residual polygons due to positional error and thus reduced the false change areas, which was most evident in the change maps. The change maps after using this procedure better reflected the true changes. A method of identifying them based on their position within a buffer of a given width and then eliminating them by joining them to a neighbouring polygon was proposed as the most appropriate method for removing sliver polygons in overlay analyses.Conclusions Old large-scale maps are a very valuable source of historical data and have a place in landscape studies, especially when researching smaller areas, such as municipalities or cadastres, where they allow work at the level of land parcels. It has been confirmed that the positional inconsistency of map sources can be eliminated to a certain extent by the chosen time series vectorization procedure. Considering the type of study, the type of spatial data used, and the type of results that characterise the change in the area, it is advisable to choose an adequate method for refining the results.
Impact of Varying Coronavirus Regulations on Green-industry Sales
Authors: Paonessa Dominic B. , Campbell Julie H. , Secor William , Campbell Benjamin L.
Published: April 2024

In 2020, the COVID-19 pandemic changed the way many businesses conducted business. Notably, regulations imposed by states impacted how green-industry firms sold their plants and landscape products. However, not all states implemented the same stringency of regulations. Using an online consumer survey implemented in Jan 2021, we examine the impact of varying regulation stringencies across five treatment groups (Michigan, and New York, and low, medium, and high stringency). We estimate the difference between 2020 and 2019 self-reported expenditures, in conjunction with propensity score matching to compare each treatment with the other treatments. Results indicate that, for the most part, states with greater stringency associated with their COVID regulations did not impact plant and landscape expenditures negatively between 2019 and 2020. However, Michigan consumers did spend significantly less than medium- and high-stringency states for landscape products. Michigan was one of only two states that put qualifications on green-industry firms, and it was the only state to list green-industry firms as nonessential. Also, New York consumers spent more than low-stringency states, and low-stringency states spent less than high-stringency states for plants. Furthermore, there were no differences in online expenditures between state treatment groups. From a policy perspective, regulation type (i.e., shutting down green-industry sectors as Michigan did) had varying impacts across product categories within the green industry.
Integration of objective weighting methods for criteria and MCDM methods: application in material selection
Authors: Dua Tran Van , Duc Duong Van , Bao Nguyen Chi , Trung Do Duc
Published: April 2024

Determining weights for criteria is an extremely crucial step in the process of selecting an option based on multiple criteria, also known as Multi-Criteria Decision Making (MCDM). This article presents the combination of five objective weighting methods for criteria with three MCDM methods in the context of material selection. The five objective weighting methods considered are Entropy, MEREC (Method based on the Removal Effects of Criteria), LOPCOW (Logarithmic Percentage Change-driven Objective Weighting), CRITIC (Criteria Importance Through Intercriteria Correlation), and MEAN. The three MCDM methods employed are MARA (Magnitude of the Area for the Ranking of Alternatives), RAM (Root Assessment Method), and PIV (Proximity Indexed Value). Material selection investigations were conducted in three different cases, including lubricant selection for two-stroke engines, material selection for manufacturing screw shafts, and material selection for manufacturing gears. The Spearman's rank correlation coefficient was calculated to assess the stability of ranking the alternatives using different MCDM methods. The combinations of objective weighting methods and MCDM methods were evaluated based on factors such as consistency in identifying the best material type, range, average value, and median of each set of Spearman's rank correlation coefficients. Two significant findings were identified. First, the weights of criteria calculated using LOPCOW method appear to be inversely related to those calculated using the Entropy method. Second, among the three MCDM methods used, MARA was identified as the most suiTable for lubricant selection for two-stroke engines, RAM was found to be the most suiTable for material selection for screw shafts and gears. The best material type in each case was also determined
Experimental investigation of turbulent flow through a square-sectioned duct and 90ᵒ square elbow by using circular turbulator
Authors: Putra Randi Purnama , Sutardi  , Widodo Wawan Aries , Yuvenda Dori , Lapisa Remon , K. Arwizet , Krismadinata  , Harmanto Dani
Published: April 2024

The ducting system is made up of 90° elbows and a few other fittings and accessories in addition to straight ducts. The friction loss, separation loss, and secondary flow loss are the main causes of the pressure decrease in an elbow, and they all increase with the presence of elbows. Utilizing too much energy to propel the flow is a cost associated with pressure loss. The aim of this research is to investigate turbulent flow via 90° square elbows and a square-sectioned duct through experimental methods by adding a circular turbulator (CT) close to the elbow wall's inner radius. The Reynolds numbers (ReDh) used in this research are 1.6×104, 4.8×104, and 9.5×104, with average flow velocities of 2 m/s, 6 m/s, and 12 m/s. Circular turbulators are added to the inner walls with angular positions (α) of 5°, 10°, 15°, and 20°. The results showed that the turbulence intensity increased toward the inner radius wall of the elbow in ducting with CT. For this study, the flow within the ducting with the CT is generally more turbulent than the flow inside the ducting without the CT. By including CT, it was possible to reduce the overall pressure loss in ducting with an elbow. The pressure reduction at two ReDh values (1.6×104 and 4.8×104) was only lessened by CT positioned at α=10°, 15°, and 20° out of the four CT placements. Conversely, CT positioned at α=5° can only effectively mitigate pressure decrease at ReDh=1.6×104. CT installation cannot lessen the pressure drop that happens in the ducting at a value of ReDh=9.5×104. CT placement at the three α values often helps to lower the pressure drop in the ducting. Using the CT, positioned at α=15°, is the greatest strategy to reduce the overall pressure decrease
Photon-photon fusion and tau g-2 measurement in ATLAS
Authors: Ogrodnik Agnieszka
Published: April 2024

Relativistic heavy-ion beams at the LHC are accompanied by a large flux of equivalent photons. New measurements of exclusive dilepton production (electron, muon, and tau pairs) performed by the ATLAS experiment are discussed. We present the photon-induced production of tau pairs and constraints on the tau lepton’s anomalous magnetic dipole moment. In addition, measurements of photon-induced electron and muon pair production are presented, which provide strong constraints on the nuclear photon flux and its dependence on the impact parameter and photon energy. Forward neutrons are utilised to provide an experimental handle on the impact parameter range sampled in the events.
Recent ATLAS results on forward physics and diffraction
Authors: Staszewski Rafał
Published: April 2024

The ATLAS detector at the LHC is equipped with dedicated systems designed for the detection of forward protons produced in diffractive and photon-induced processes. These detectors significantly extend the ATLAS physics reach. Recent measurements performed using these forward proton detectors: elastic proton-proton scattering, exclusive charged pion-pair production, and two-photon production of lepton pairs are presented.
Intermittency analysis of charged hadrons generated in Pb-Pb collisions at $\sqrt{s_{NN}}$= 2.76 TeV and 5.02 TeV
Authors: Malik Salman Khurshid , Gupta Ramni
Published: April 2024

Local density fluctuations are expected to scale as a universal power-law when the system approaches critical point. Such power-law fluctuations are studied within the framework of intermittency through the measurement of normalized factorial moments in (\etaη, \phiϕ) phase space. Observations and results from the intermittency analysis performed for charged particles in Pb-Pb collisions using PYTHIA8/Angantyr at 2.76 TeV and 5.02 TeV are reported. We observe no scaling behaviour in the particle generation for any of the centrality studied in narrow p_TT bins. The scaling exponent \nuν shows no dependence on the centrality ranges.
Reutilização e prática de uso de máscaras entre universitários
Authors: De Souza Layane Trindade , Freire Maria Eliane Moreira , Nogueira Wynne Pereira , Ferreira Brasil Maria Hellena , Costa Sérgio Eduardo Jerônimo , Ávila Fernanda Maria Vieira Pereira , De Oliveira e Silva Ana Cristina
Published: April 2024

O estudo teve como objetivo analisar a prática do uso de máscaras e os fatores associados entre estudantes universitários da Paraíba durante a pandemia da covid-19. Trata-se de um estudo do tipo transversal, analítico, desenvolvido em instituição de ensino público do estado da Paraíba com 404 estudantes universitários. Os dados foram coletados por meio de um questionário estruturado e utilizou-se a escala Face Mask Use Scale, versão para o Português do Brasil. Os dados foram analisados por meio de estatística descritiva, testes de normalidade, testes U de Mann-Whitney e Kruskal-Wallis. O escore geral da prática do uso de máscaras foi de 23,7 (Desvio padrão=4,9). A utilização de máscaras em ambientes de saúde obteve maior escore 9,2 (Desvio padrão=1,6). Renda mensal, diagnóstico de covid-19, isolamento e uso de drogas ilícitas foram fatores associados ao uso de máscaras. É visto que estudantes universitários possuem práticas deficientes tanto na reutilização de máscaras quanto no uso delas em ambientes públicos e domiciliares.
Covid-19 entre idosos: perfil das internações segundo sexo
Authors: Duarte Lívia Mio , Marchiori Gianna Fiori , Marmo Flavia Aparecida Dias
Published: April 2024

Objetivo: Comparar os aspectos demográficos e clínicos com o desfecho (cura ou óbito) das internações de COVID-19 entre idosos segundo sexo. Métodos: Trata-se de um estudo ecológico, com análise do perfil dos indivíduos idosos, notificados com COVID-19 em Minas Gerais. Foram utilizados dados oriundos da Ficha de Registro Individual dos casos de Síndrome Respiratória Aguda Grave Hospitalizado a partir de 09 de março de 2020, referente a primeira notificação em idoso do Estado de Minas Gerais no banco, à 08 de março de 2022. A amostra final foi composta por 83.808 notificações de idosos com diagnóstico de COVID-19. Foi realizada análise descritiva e teste qui quadrado no Statistical Package for the Social Sciences (SPSS). Resultados: O perfil encontrado entre os idosos que evoluíram para óbito evidenciou que os homens tinham 80 anos ou mais e as mulheres 70├80 anos; ambos eram brancos, moravam na zona urbana, apresentavam fatores de risco, fizeram o uso de suporte ventilatório não invasivo e apresentaram necessidade de internação na Unidade de Terapia Intensiva. Conclusão: Nota-se uma diferença de idade entre os idosos homens e mulheres na evolução para óbito, enquanto as demais características foram semelhantes. Este fato possibilita a reflexão dos impactos na saúde em diferentes grupos de indivíduos.
YAŞLI BİREYLERİN YERİNDE YAŞLANMA DÜZEYLERİ İLE YAŞAM KALİTESİ DÜZEYLERİ ARASINDAKİ İLİŞKİNİN İNCELENMESİ
Authors: Gelen Tevfik
Published: April 2024

Bu çalışma yaşlı bireylerin yerinde yaşlanma ve yaşam kalitesi düzeyleri arasındaki ilişkiyi incelemek amacıyla gerçekleştirilmiştir. Bu temel amaç doğrultusunda ise, yerinde yaşlanma ve yaşam kalitesi düzeyleri, bu düzeylerin bazı bağımsız değişkenlere göre anlamlı olarak farklılaşıp farklılaşmadığı ve yaşlı bireylerin yerinde yaşlanma düzeylerinin yaşam kalitesi düzeylerini anlamlı bir şekilde yordayıp yordamadığı incelenmiştir. Araştırmanın örneklemini Kahramanmaraş’ın Türkoğlu ilçesinde ikamet eden ve uygun örnekleme yöntemiyle seçilen 65 yaş ve üstü 157 kişi oluşturmaktadır. Araştırmada veri toplama araçları olarak demografik bilgi formu, Yerinde Yaşlanma Ölçeği (YYÖ) ve Yaşam Kalitesi Ölçeği (YYK-Kısa) kullanılmıştır. Verilerin analizinde frekans, ortalama, standart sapma, t test, ANOVA ile Pearson Çarpımı korelasyon katsayısı ve basit regresyon analizi teknikleri kullanılmıştır. Araştırma sonucunda yaşlı bireylerin YYK-Kısa’dan aldıkları puanlar ile YYÖ ve tüm alt boyutlarından aldıkları puanlar arasında pozitif yönde, orta düzeyde anlamlı bir ilişki bulunmuştur. Ayrıca yaşlı bireylerin YYÖ düzeylerinin yüksek, YYK-Kısa düzeylerinin çok yüksek olduğu belirlenmiştir. Yaşlı bireylerin YYÖ düzeylerinin YYK-Kısa düzeylerini anlamlı olarak etkilediği tespit edilmiştir. Yaşlı bireylerin YYÖ ve YYK-Kısa düzeylerine ilişkin görüşlerinde cinsiyet ve yaş değişkenlerine göre farklılaşmadığı; medeni durumu, yaşadığı yerleşim alanı, ikamet ettiği evin mülkiyeti, kiminle yaşadığı, öğrenim durumu, sağlık durumu, evde bakım hizmeti alma durumu ve gelir düzeylerinin bazı alt boyutlar ve ölçek toplamında farklılaştığı belirlenmiştir.
Aprígio Gonzaga e Oscar Wanderley
Authors: Azevedo Laís Paula de Medeiros Campos , Medeiros-Neta Olívia Morais de
Published: April 2024

Este trabalho discute as ideias de Aprígio de Almeida Gonzaga (São Paulo) e Oscar Wanderley (Rio Grande do Norte) a partir da escrita em revistas pedagógicas publicadas na década de 1920. Analisamos três textos dos autores publicados na Revista da Educação de São Paulo e na Revista Pedagogium. Os intelectuais foram normalistas, professores e representantes de instituições de educação profissional. Seus textos circularam na impressa pedagógica do Rio Grande do Norte no período. Investigamos seus lugares de fala e a relação construída entre suas práticas profissionais e a escrita sobre a educação profissional (Certeau, 1982). Estes intelectuais situam-se em um contexto de criação de instituições com o objetivo de fornecer uma educação profissional para crianças, jovens e adultos (Cunha, 2000; Manfredi, 2017). A partir da análise, destacamos as influências da literatura estrangeira, a ênfase no aprender fazendo e no valor do trabalho na construção de cidadãos para um novo Brasil.
Effect of Iron Deficiency Anemia on Blood Glucose and Insulin
Resistance in Women with Type II Diabetes: A Single-group, Clinical
Interventional Study
Authors: Parham Mahmoud , Tavasoli Gholam Reza , Arsang-Jang Shahram , Habibi Mohammad Amin , Dameshgi Davood Olad , Pashaei Mohammad Reza , Ahmadpour Sajjad , Vafaeimanesh Jamshid
Published: April 2024

Aims:

Iron deficiency anemia (IDA) is one of the disorders recently associated with an
increase in insulin resistance (IR) and, consequently, diabetes mellitus (DM) affection by causing
oxidative stress. In this study, we look at how IDA may contribute to developing type II diabetes
mellitus (T2DM), controlling diabetes, and reducing IR in women with T2DM.

Methods:

In this single group, clinical interventional study, we enrolled 40 women with T2DM
and IDA. Before and after intervention with ferrous sulfate tablets, their blood glucose (BG) levels
and IR levels were evaluated. This study was approved by the Ethics Committee of Qom University
of Medical Sciences (ethics code: IR.MUQ.REC.1397.031) and registered at the Iranian
Center for Clinical Trials (No. IRCT20170215032587N3). A significant level was considered p
< 0.05.

Result:

The mean age of patients was 48.18 ± 4.6 years, with 5.3-5.8 years duration of T2DM. After
the intervention, the mean fasting blood glucose (FBG) level reached 198.53 ± 48.11 to 170.93
± 37.41, which was significant (p < 0.0001). Also, hemoglobin A1C level reached from 8.49 ± 0.9
to 7.96 ± 0.58, which was significant (p < 0.0001). Homeostatic Model Assessment of Insulin Resistance
(HOMA-IR) demonstrating a significant reduction of IR levels after intervention with ferrous
sulfate tablets (p < 0.018).

Conclusions:

IDA treatment in patients with T2DM can significantly reduce the BG and IR levels.
To better control BG, checking iron status and its correction may provide better clinical outcomes
in these patients.

Clinical Trial Registration Number:

IRCT20170215032587N3.
Validations of sensory overall acceptability optimizations on response surface methodology through just-about-right technique for coffee-leaf tea at different brewing methods
Authors: Fibrianto Kiki , Arya Bimo Igoy , Muna Sofa Atika , Putri Azalea , Amelia Devia , Rachma Lalilika Ovirista , Putri Genbrovit Irha , Izzul Haq Ahmad
Published: April 2024

Response Surface Methodology (RSM) has been widely employed for optimizing processes. However, the implementation of RSM in sensory studies is still limited. Moreover, most publications implementing RSM on sensory disregarded the validation stage as normally applied for process optimization. In this study, validating sensory overall acceptability with RSM was proposed by the Just-About-Right (JAR) technique. Coffee-leaf tea has great commercial potential as an ethnic beverage with unique sensory attributes but is still underutilized. Optimizing sensory acceptability level by modifying temperature and duration of brewing using the RSM was expected to obtain well-accepted coffee-leaf tea. Robusta coffee leaf tea is brewed using combined Decoction - V60, French Press, combined French Press - V60, and V60 at 90oC to 100oC for 2 to 10 minutes. Evaluated by 110 untrained panelists, it was observed that the ideal brewing parameters for each technique were 96.6oC for 6.5 minutes for Decoction – V60, 96oC and 6.5 minutes for French Press, 90oC and 2 minutes for French Press - V60, and 90oC and 2 minutes for V60. All optimum brewing conditions based on RSM were successfully validated by overall acceptability on JAR (p-value 0.05). Thus, the JAR technique can enhance the overall sensory acceptability analysis and optimization.