bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Multi-Scale Remote Sensing for Heritage Monitoring through Integration of Satellite SAR, Laser Scanning, and Drones
Authors: Fu Lang , Seo Hyungjoon 
Published: May 2024

Abstract

Due to advancements in digital mapping and remote sensing technology, monitoring built heritage has become more straightforward and convenient. Current individual measurements have numerous limitations, leading to their underutilization. This study suggests a multi-scale data monitoring approach for detecting built heritage deformation by integrating low-cost, wide-area satellite SAR data, high-precision laser scanning technology, and drones surveying technology for quick deployment and computation. Settlement monitoring of Sizergh Castle was conducted to assess the feasibility of the proposed method. The results indicate that the method outlined in this paper can effectively and precisely monitor the settlement and deformation of the heritage building both indoors and outdoors. It can also identify the primary settlement and deformation areas within the building. This greatly improves the efficiency of monitoring heritage buildings and facilitates conservation and repair by maintenance staff.
Host-Guest-Induced Electronic State Triggers Two-Electron Oxygen Reduction Electrocatalysis
Authors: Long Xiaojing , Chen Hongni , Wang Chao , Wu Han , Li Lili , Xing Yali , Zhang Chuanhui 
Published: May 2024

Abstract

Supramolecular polymers hold promising application prospects in catalysis due to their distinctive molecular recognition and dynamic crosslinking features. However, investigating supramolecular organic electrocatalysts with high efficiency in oxygen reduction reaction (ORR) to hydrogen peroxide (ORHP) remains an unexplored frontier. Herein, we present organic polymers for ORHP by introducing cyclodextrin-containing noncovalent building blocks, and the skeleton electronic environment is further regulated via a host-guest chemistry strategy, affording HG-CD-Ph and HG-CD-TPB with abundant dynamic bonds. The oxygen intermediate desorption and electronic states are well-modulated through the host-guest decoration, resulting in appropriate regional electron binding force and controllable chemical activity. Notably, the introduction of supramolecular host-guest units into the polymer model P-CN-Ph achieves an ultra-high production rate of 9.14 mol g−1 cat h−1, and demonstrates an excellent Faraday efficiency of 98.01%, surpassing most reported metal-free electrocatalysts. Supported by theory calculation and in situ FT-IR experiment, it is revealed that C atoms (site–1) adjacent to –C=N (N) group are potential active sites. Moreover, the dynamic bonds in supramolecular catalysts can effectively regulate the binding ability of oxygen and its intermediates, leading to high reactivity and selectivity for the 2e− ORR. This work pioneers host-guest strategy and provides inspiring ideas for the ORHP process.
Physical cellular automata and artificial fish swarm fusion catastrophic failure prediction of brittle-like materials
Authors: Sun Bin , Guo T 
Published: May 2024

Abstract

The investigation aims to establish a physics-informed data-driven method for catastrophic failure analysis of brittle-like materials based on the strategy of the physical cellular automata and artificial fish swarm fusion prediction. Based on the method, local mesoscopic elasticity modulus and damage distribution of brittle-like materials can be predicted based on the monitored data of the global macroscopic mechanical response. In the data-driven prediction process based on the simplification of the artificial fish swarm algorithm, physical catastrophic failure mechanisms can be considered by utilizing a modified cellular automata technique for updating and iterating damage distribution based on the principle of energy conservation and energy dissipation. Two numerical cases are implemented to support the developed method. The results support that the method possesses a good convergence and a high prediction accuracy. The maximum prediction error of the macroscopic stress-strain relationship of the two numerical cases is 9.6% based on the optimal mesoscopic elasticity modulus prediction. Meanwhile, the predicted local mesoscopic catastrophic failure paths of the two numerical cases both match well with the corresponding experimental results. The developed physics-informed data-driven method can provide an efficient tool to predict both macroscopic and mesoscopic failure particularities of brittle-like materials for better investigating their catastrophic failure mechanisms.
Optimal Estimation of Power Chris-Jerry DistributionParameters Using Ranked Set Sampling Design withApplication
Authors: Alsadat Najwan , Hassan Amal S. , Elgarhy Mohammed , Nagarjuna Vasili B. V. , Benchiha Sid Ahmed , Gemeay Ahmed M. 
Published: May 2024

Abstract

Effective sample design has a major role in the quality of parameter estimation in statisticalparameter estimation issues. The ranking set sampling (RSS) strategy is effective and a less costlyoption than simple random sampling (SRS). A novel mixture continuous lifetime distribution thathas been proposed recently is the power Chris-Jerry distribution (PC-JD). It is useful for modelinga number of real data sets. This paper investigates the RSS approach for estimating the PC-JD’sparameters. There are roughly sixteen different techniques of estimation that are used, such as themaximum likelihood method, the percentiles method, some methods based on minimum distance,the Kolmogorov method, and some methods based on minimum and maximum spacing distances. Incomparison to a SRS, the simulation research assesses the performance of the suggested RSS-basedestimates in terms of some measures of accuracy. To identify the optimal estimating strategy, thepartial and overall ranks of many estimates are shown. According to numerical results, the maximumlikelihood approach seems to be quite beneficial in evaluating the estimated quality of RSS and SRS.RSS is a more effective sampling approach than SRS owing to its better efficiency. Additionally, thedifferent estimation techniques with survival data for both sampling techniques are examined
MnFe2O4@L-Cysteine as a drug delivery system, in vitro cytotoxicity evaluation on human Breast cancer cell (MCF7) and DFT calculation
Authors: hasankhani Neda , Hosseini Sharieh , Askarizadeh Elham , mehravi Bita 
Published: May 2024

Abstract

Thanks to their high hydrophilic and magnetic properties, MnFe2O4 nanoparticles (NP) are recognized as favorable drug carriers. In this study, L-Cysteine-modified MnFe2O4 nanoparticles (MnFe2O4@L-Cysteine) were prepared and characterized. Their cytotoxicity against human breast cancer cell lines (MCF7) was also evaluated by MTT assay. To simulate drug delivery systems, the interaction between modified NP and 5-fluorouracil (5-FU) was examined as a breast cancer drug. The MTT results showed the applicability of MnFe2O4@L-Cysteine nanoparticles as a potential cytotoxic agent in breast cancer treatment. Based on the theoretical calculations, the adsorption energy between L-Cysteine and 5-FU was − 12.029 KJ/mol and their interaction was spontaneous and exothermic at the temperature range of 278.15 to 288.15 K. Also, the drug release thermodynamically is feasible at body temperature. The calculated electronic descriptors indicated that the electrons were transferred from L-Cysteine to 5- FU. Overall, MNFe2O4@L-Cysteine, in addition to being non-toxic has the potential to deliver 5-FU anticancer drug.
Dynamics of optical solitons and sensitivity analysis in fiber optics
Authors: Raees Nida , Mahmood Irfan , Hussain Ejaz , Younas Usman , Elansary Hosam O. 
Published: May 2024

Abstract

The nonlinear Schrödinger equation (NLSE) and its various forms have significant applications in the field of soliton theory. The Fokas-Lenells (FL) equation stands as a cornerstone in deepening our understanding of nonlinear wave dynamics within optical systems, particularly concerning the behavior of ultrashort pulses across different media. Its significance lies in providing a comprehensive framework to study and analyze complex phenomena, ultimately contributing to advancements in optical technology and applications. The FL equation is an integrable extension of the NLSE that provides a description of the nonlinear propagation of pulses in optical fiber. This paper seeks to discover optical soliton solutions for the FL equation by employing a modified sub-equation method. Additionally, the sensitivity analysis is described by using the various initial conditions. For the physical behavior of the models, some solutions are graphically shown in 2D, 3D and contour graphs by assigning specific values to the parameters under the provided situation at each solution. As a result, we discovered several new families of exact traveling wave solutions, such as bright solitons, dark solitons, and combined bright and dark soliton. As a result, investigated solutions have significant advantages in the field of mathematical physics.
Mathematics subject classification (2020) : 39A1; 39B62; 33B10; 26A48; 26A51
GIS-Based Erosion Susceptibility Analysis in Bingöl (Türkiye): A Comparasion of Logistic Regression, Frequency Ratio, Weight of Evidence and Shannon’s Entropy models
Authors: İNİK Orhan , UTLU Mustafa 
Published: May 2024

Abstract

Soil erosion is one of the most important and critical processes occurring in Turkey, as in all parts of the world. It is of great importance to understand the processes that occur as soil erosion continues. The aim of this study is to determine the erosion susceptibility occurring in the Çapakçur Stream basin, one of the important erosion areas of Turkey. In the study, erosion susceptibility analysis was used using 19 conditioning factors based on 4 different methods (Shannon Entropy (SE), Logistic Regression (LR), Frequency Ratio (FR) and Weight of Evidence (WoE)), which are actively used today in erosion susceptibility analysis and determination of critical areas in terms of erosion. has been made. Model performances of the Analysis Results were evaluated based on a data set of 840 training (70%) points and 360 validation (30%) points using ROC and AUC values.. According to result of the ROC and AUC values show that Logistic regression seems to perform well on both training (AUC = 94.7%) and validating datasets (AUC = 93.5%). On the other hand, Weight of Evidence training (AUC = 93.5%) and testing datasets (AUC = 91.4%), Frequency Ratio training (AUC = 93.5%) and testing datasets (AUC = 92.4%). of the Weight of Evidence resault show that AUC and ROC values smilar to Logistic Regression result, but slightly lower than Logistic Regression. Additionally, Shannon Entropy shows that it performs lower than other methods on both training (AUC = 55.7%) and testing datasets (AUC = 56.3%). Conducting analyzes based on these methods, especially in erosion susceptibility studies, will facilitate both planning and the accuracy of the results obtained.
On representations and topological aspects of positive maps on non-unital quasi *- algebras
Authors: Bellomonte Giorgia , Djordjevic Bogdan , Ivkovich Stefan 
Published: May 2024

Abstract

In this paper we provide a representation of a certain class of C*-valued positive sesquilinear and linear maps on non-unital quasi *- algebras, thus extending the results from [\cite{GBSICT}] to the case of non-unital quasi *-algebras. Also, we illustrate our results on the concrete examples of non-unital Banach quasi *-algebras, such as the standard Hilbert module over a commutative C*-algebra, Schatten p-ideals and noncommutative $L^2$-spaces induced by a semifinite, nonfinite trace. As a consequence of our results, we obtain a representation of all bounded positive linear C*-valued maps on non-unital C*-algebras. We also deduce some norm inequalities for these maps. Finally, we consider a noncommutative $L^2$-space equipped with the topology generated by a positive sesquilinear form and we construct a topologically transitive operator on this space.
MSC 2020: 46K10, 47A07, 16D10, 37Bxx, 47G10.
Preparation of Na 2 FeO 3 and Application in Wastewater treatment
Authors: Guo Haoda , Fan Linhao , Zhang Naidong 
Published: May 2024

Abstract

Na2FeO3 serves as a highly effective water-purifying agent and exhibits superior performance compared with ferrate(VI). The traditional synthesis method of ferrate(IV) requires that the conditions required for the reaction are difficult. This study focuses on the environment-friendly synthesis of green Na2FeO3 crystals using sodium hypochlorite as a medium via a concentration method under depressurization. Green crystallization was meticulously characterized and identified as Na2FeO3 using infrared spectroscopy, UV/Vis spectroscopy, Mössbauer spectroscopy, and X-ray diffraction techniques. This investigation delves into the effect of varying the concentrations of Fe2(SO4)3, NaOH, NaClO, and the reaction temperature on the yield of Na2FeO3, which is apparently lower than that of the traditional method. This study provides important theoretical support for large-scale production of Na2FeO3. In addition, Na2FeO3 was shown to be superior to K2FeO4 in the treatment of oil-recovery wastewater.
Mechanism of Micro and Nanoplastics Formation from Semicrystalline Polymers
Authors: Kumar Sanat , Mendez Nicholas , Sharma Vivek , Valsecchi Michele , Adhikari Sabin , Pai Vighnesh , SriB Gorugantu , Broadbelt Linda , Schadler Linda , Muller Alejandro , Watson Shelby , Dadmun Mark , Kumaraswamy Guruswamy 
Published: May 2024

Abstract

It is well-established that micro and nanoplastics (MNPLs) are released from polymers through environmentally triggered bond breaking. However, the mechanism by which this Å-level process leads to nm-m sized fragments is poorly enunciated. Through experimental studies on three distinct chemistries, we demonstrate that only polymers with a semicrystalline morphology produce MNPLs under quiescent conditions. In this morphology, comprised of alternate crystalline and amorphous domains, chain scission occurs faster in amorphous regions. Through theoretical arguments, we show that tie molecules and bridging entanglements (“connectors”), which provide structural integrity to the semicrystalline structure by connecting two adjacent crystals, are preferentially broken. We propose that the cleavage of a threshold amount of connectors (i.e., scission of as little as 1% of chain bonds), leads to the spontaneous release of MNPLs. The resulting fragments comprise highly polydisperse stacks of lamellae, with an individual lamella – several nanometers thick - being the building block. Degradation of the crystals occurs over much longer time scales, explaining the environmental persistence of MNPLs, even under non-quiescent conditions. Since ~70 % of polymers are semicrystalline, engineering connectors may represent an effective strategy to reduce MNPL release rates.
Husbandry Practices, Reproductive and Production Performanceof Indigenous Goats in Ahferom District, Tigray, Northern Ethiopia
Authors: Asmelash Hiwot , Woldegebriel Daniel , Gebremariam Tikabo , Begashaw Teshome 
Published: May 2024

Abstract

A study, conducted in Ahferom district (Tigray), Northern Ethiopia, aimed to investigate indigenous goats’ husbandry practices, productive and reproductive performances, and constraints. Two Tabias from midland and one from lowland in the district were purposively selected based on their potentiality. Twenty-four household (HH) goat keepers, eight from each Tabia, were randomly selected. A pretested semi-structured questionnaire wasused to gather data. Focus group discussions were also held with knowledgeable farmers and key informants. The collected data was analyzed using SPSS statistical software Version 28.0. In the study area, the goat flock structure (16.6±3.5) consisted of does (4.7±1.4), bucks (1.6±0.9), doe kids (3.6±1.2), and buck kids (2.9±0.8). The overall mean litter size, age at first kidding and kidding interval were 2.06±0.13, 12.9±0.2 years and 7.6±0.5 months, respectively. The mean amount of milk produced/day from a lactating goat was estimated to be 0.2 liters. Goats were kept by smallholder farmers for sale (52.5%), home consumption (24.4%), saving (13.1%), manure (10%), and prestige (1.0%) in the midland. Nevertheless, goats were kept for sale (33.3%), home consumption (33.3%), saving (12.5%), manure (16.6%), and prestige (4.1%) in the lowland. Goats in the study area were mainly dependent on browsing plants in both wet and dry seasons. The overall sources of water in the study area were water wells (40.1%), hand pumps (32.7%), and ponds (27.2%). Most (89.8%) farmers used separate houses for their goats. Diseases, drought, predators, inadequate extension support, feed and water shortages were the most important problems identified in the study area.
Learning-oriented assessment of L2 argumentative writing ability: Its impacts on EFL undergraduate students’ writing ability and academic resilience
Authors: Imsa-ard Pariwat 
Published: May 2024

Abstract

The notion of utilizing assessment to facilitate learning has garnered significant momentum in language education. Nevertheless, a substantial portion of the pertinent theoretical and research literature tends to concentrate on the dynamics of the teaching-learning interface, often neglecting the critical role of effective teacher and peer interaction in augmenting student learning. The current study explored the learning-oriented assessment of EFL learners’ writing ability. Specifically, the study involved the development and administration of learning-oriented writing assessment (LOWA) tasks that aimed to measure 67 learners’ ability to display competency in L2 writing ability by building an argument. In addition, the study aimed to examine whether implementing LOWA tasks can help enhance learners’ academic resilience. Following a quasi-experimental mixed-methods approach, results from the assessment administration were analyzed using robust statistical analyses and qualitative analysis of the responses. A learning-oriented approach to assessment as a design and validation framework was used to interpret qualitative and quantitative evidence. The findings revealed that the students’ L2 argumentative writing ability and academic resilience improved as a result of the LOWA tasks where the experimental group significantly outperformed the control group in the post-test. Moreover, focus-group interviews revealed favorable perspectives towards LOWA while also expressing some concerns on giving feedback. It is hoped that this research will shed light on the language assessment within complex tasks and will help understand the affordances of implementing embedded assistance in language assessment.
A district-level geospatial analysis of the availability of improved water and sanitation among tribal households in India
Authors: Mudi Prasanna Kumar , Pradhan Manas Ranjan , Saikia Daisy , De Prasenjit 
Published: May 2024

ABSTRACT

Despite progress in Sustainable Development Goal 6, which envisages clean water and sanitation for all, enormous disparities in access to water and sanitation services between and within countries continue to be a significant challenge. Evidence on the spatial heterogeneity of water, sanitation, and hygiene practices among the Scheduled Tribe (ST) population is limited in India. This study estimates the spatial heterogeneity in ST people's access to improved water and sanitation facilities and its correlates at the district level. Geospatial techniques like Moran's I, univariate and bivariate local indicator of spatial association, and spatial regression models were carried out for 707 districts covered in the fifth round of the National Family Health Survey, 2019–21. Stata was used for descriptive analysis, and ArcMap and GeoDA were used for spatial analysis. Only about half of ST households had access to improved water and sanitation facilities in India. Spatial heterogeneity across districts was evident, with 130 districts from Uttarakhand, Himachal Pradesh, Punjab, Haryana, Delhi, Sikkim, Arunachal Pradesh, Nagaland, Mizoram, and some portion of Karnataka forming the hot spots. Gender and age of the household head, family type, and region were significantly associated with improved water and sanitation facilities among ST households.
Machine Learning Models for Parkinson Disease: Systematic Review
Authors: Tabashum Thasina , Snyder Robert Cooper , O'Brien Megan K , Albert Mark V 
Published: May 2024

Abstract

Background
With the increasing availability of data, computing resources, and easier-to-use software libraries, machine learning (ML) is increasingly used in disease detection and prediction, including for Parkinson disease (PD). Despite the large number of studies published every year, very few ML systems have been adopted for real-world use. In particular, a lack of external validity may result in poor performance of these systems in clinical practice. Additional methodological issues in ML design and reporting can also hinder clinical adoption, even for applications that would benefit from such data-driven systems.

Objective
To sample the current ML practices in PD applications, we conducted a systematic review of studies published in 2020 and 2021 that used ML models to diagnose PD or track PD progression.

Methods
We conducted a systematic literature review in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines in PubMed between January 2020 and April 2021, using the following exact string: “Parkinson’s” AND (“ML” OR “prediction” OR “classification” OR “detection” or “artificial intelligence” OR “AI”). The search resulted in 1085 publications. After a search query and review, we found 113 publications that used ML for the classification or regression-based prediction of PD or PD-related symptoms.

Results
Only 65.5% (74/113) of studies used a holdout test set to avoid potentially inflated accuracies, and approximately half (25/46, 54%) of the studies without a holdout test set did not state this as a potential concern. Surprisingly, 38.9% (44/113) of studies did not report on how or if models were tuned, and an additional 27.4% (31/113) used ad hoc model tuning, which is generally frowned upon in ML model optimization. Only 15% (17/113) of studies performed direct comparisons of results with other models, severely limiting the interpretation of results.

Conclusions
This review highlights the notable limitations of current ML systems and techniques that may contribute to a gap between reported performance in research and the real-life applicability of ML models aiming to detect and predict diseases such as PD.