bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determinants of routine immunizations dropout among children less than five years of age in Ethiopia: A further multilevel analysis from mini 2019 EDHS
Authors: Tolera Moti , Birhanu Abdi , Regassa Lemma Demissie , Getachew Tamirat , Negash Abreham , Jibro Usmael , Deressa Alemayehu , Abdurahman Dureti , Motuma Aboma , Gamachu Mulugeta , Mohammed Fethia , Balis Bikila , Mussa Ibsa 
Published: September 2023

Abstract

Background
Globally, immunization prevents an estimated 2–3 million deaths from illnesses that can be prevented by vaccination. The burden of Pentavalent and Measles immunizations dropout was not investigated sufficiently. Therefore, this analysis is meant to determine the coverage, burden, and predictors of Pentavalent and Measles immunizations in Ethiopia.
Materials and methods
this study is a further analysis of Mini EDHS 2019 which was conducted with a nationally representative sample. In this study immunization data was collected from a total sample of 3208 and 2004 (34.8%) children who received pentavalent 1 were considered for this study. Univariate, Bi variate and multilevel mixed effect analysis was done using STATA version 17 Software. The mixed-effect model with the lowest AIC and BIC (information criteria) was chosen and a factor was designated as a significant predictor of immunization dropout if its p-value was less than 0.05 at 95% CI. The best-fitting model among the fitted models was ultimately chosen using the Akaike and Bayesian Information Criteria (AIC and BIC).
Result
The mean age of the head of the house hold is 37.6. Majority (68.9%) of the residents were from rural area. of the total population 64.9% have no formal education. The immunization coverage of Ethiopian children is 72.85% and 60.68% for Pentavalent 1 and Measles (fully vaccinated) respectively. From Children who started pentavalent 1 vaccination, 26.7% and 39.3% of the children dropped from taking Pentavalent 3 and measles vaccination respectively. Factors such as household wealth indexes, marital status being married, being in an age group of above 6 months, and living in Addis Ababa reduced the likelihood of pentavalent 3 vaccine dropout and living in Afar compared to Tigray. expose a child to drop from Pentavalent 1. Religion, family size, and living in the Afar region increased the likelihood of measles dropouts compared to their counterparts whereas, children aged above one year was prevented from dropping from measles dropout compared to those aged nine months to one year.
Conclusions
Immunization coverage among Ethiopian children was low and the dropout from pentavalent 1 and measles vaccination is high compared the national and international targets to improve immunization coverage and reduce dropout. So different cost-effective interventions like Education provision for community, decision-making facilitation, behavioral change support, multi-system participation were requited to increase vaccination coverage and reduce the vaccine dropout among children in Ethiopia.
Reversal of Bertrand-Cournot Ranking for Optimal Privatization Level
Authors: Paul Arindam , De Parikshit 
Published: September 2023

Abstract
We analyze a mixed duopoly market with a public and a private firm competing in the downstream market. The public firm is partially privatized and a regulator decides on the privatization level to maximize welfare. A foreign monopolist supplies a key input for producing the final commodity, and may use uniform or discriminatory pricing; we observe the presence of a foreign monopolist that practices price discrimination can lead to the privatization of a public firm. The overall findings show, that under uniform pricing, Cournot competition leads to higher privatization levels, while under discriminatory pricing, Bertrand competition leads to higher privatization levels. The sensitivity of Cournot-Bertrand rankings to substitutability depends on the pricing regime.
JEL classification code: D4, D6, H4, L1,L2
A New Hybrid Particle Swarm Optimization-Teaching Learning Based Optimization for Solving Optimization Problems
Authors: Matoušová Ivana , Trojovský Pavel 
Published: September 2023

Abstract
This research paper develops a novel hybrid approach, called hybrid Particle Swarm Optimization-Teaching Learning Based Optimization (hPSO-TLBO), by combining two metaheuristic algorithms to solve optimization problems. The hPSO-TLBO approach integrates the exploitation capabilities of PSO with the exploration abilities of TLBO, resulting in a synergistic combination. The algorithm is presented in detail, accompanied by a comprehensive mathematical model. A group of benchmarks is used to evaluate the effectiveness of hPSO-TLBO, covering various types such as unimodal, high-dimensional multimodal, and fixed-dimensional multimodal. In addition, CEC 2017 benchmark problems are also utilized for evaluation purposes. The optimization results clearly demonstrate that hPSO-TLBO performs remarkably well in addressing the benchmark functions. It exhibits a remarkable ability to explore and exploit the search space while maintaining a balanced approach throughout the optimization process. Furthermore, a comparative analysis is conducted to evaluate the performance of hPSO-TLBO against twelve widely recognized metaheuristic algorithms. The evaluation of the experimental findings illustrates that hPSO-TLBO consistently outperforms the competing algorithms across various benchmark functions, showcasing its superior performance. The successful deployment of hPSO-TLBO in addressing four engineering challenges highlights its effectiveness in tackling real-world applications.
A Robust High Gain Integrated Z source SEPIC Converter for PV Applications
Authors: Purushothaman S K , Sattianadan D 
Published: September 2023

Abstract
In this research article, the technique of integration is considered to enhance the performance and voltage gain of the Single Ended Primary Inductor Converter (SEPIC). Since, the current energy scenario focuses on maximizing the usage of Photovoltaics (PV) systems and Electric Vehicles (EVs), which support low-to-zero carbon emission. The role of an effective DC-DC converter design becomes crucial owing to their significance as power regulators in both these applications. So far, numerous high-gain converter topologies have been published, but these topologies have complex structures, which are bulky and expensive. Hence a cost-effective converter design capable of achieving high voltage gain is proposed in this work by integrating a Z-source converter to SEPIC. The Z-source converters are highly reliable with a wide voltage conversion range, lower ripple current, and minimum in-rush current, whereas the SEPIC converter comes with the benefits of input-output isolation, non-inverted output voltage polarity, and continuous input current. Moreover, the mathematical modeling, modes of operation, and voltage stress of the suggested converter design are also presented in the article. Additionally, the Cascaded Fuzzy Logic Controller (CFLC), effective in delivering quick accurate error compensation is employed in this work for sustaining the constant converter output. The results from MATLAB simulation and lab-scaled prototype execution credibility to the operation of the suggested converter as it achieves an impressive 97% efficiency.
Housing Quality Index Analysis at the Urban Axis Level in Eastern and Western Europe Using Ses Analysis Case Study: Bistrita-Cluj-Napoca -Debrecen-Békéscsaba- Bourges- Chateauroux -Pamplona -Zaragoza
Authors: Tătar Marius Alexandru , Bâca Ioan 
Published: September 2023

Abstract
The size of the home is considered the most critical issue affecting the quality of life. This can be measured by the quality of the house and its environment. This paper highlights the housing quality index at the urban axis level the urban axes of Western and Eastern Europe and the impact of socioeconomic activities on the index. The Household Quality of Life Index (HQLI) was calculated using 11 variables. Household quality of life comprises two distinctive indices: the Housing Conditions Index (HCI) and the Asset Possession Index (API). The study found a variation in the housing condition variables across the urban focus areas. The impact of the socioeconomic environments is disproportionately dependent on the social-economic profile of the urban environments that make up the Urban Axis and the related economic activities that take place in the area of influence in the administrative-territorial units and the variability of the Housing Conditions Index This can be measured by the quality of the house and its environment. This paper highlights the housing quality index at the urban axis and the impact of socioeconomic activities on this index.
The study area comprises territories in the urban axis in Western Europe and the urban axis in Eastern Europe. The socio-economic context of the area has been the basis for understanding the patterns of evolution identified in the urban landscape and being a driver in ongoing urban transformations and processes. The impact of the socio-economic is disproportionate to the socioeconomic profile of the urban environments that make up the Urban Axis and the economic activities related to the economic activities taking place in the catchment area in the administrative-territorial units, hence the variability of the Housing Conditions Index which is a system Housing Quality Indicator (HQI) is a tool for measuring and evaluating housing systems based on quality and not just cost.
Antibacterial mechanism of rose essential oil against Stenotrophomonas maltophilia, a metabolomic study
Authors: Yuan Yu-Han , Wang Wen-Liang , Liu Ling-Xiao , Guo Li , Li Xing-Jiang , Liu Yun-Guo 
Published: September 2023

Abstract
Stenotrophomonas maltophilia (S. maltophilia) is a spoilage microorganism widely distributed vegetables, dairy products, and various environments, and can cause serious foodborne illnesses. Rose essential oil is widely recognized as an exceptional natural antibacterial agent, renowned for its environmentally friendly, safe, and non-toxic properties. In the present study, we conducted a comprehensive analysis to elucidate the inhibition mechanism of rose essential oil against S. maltophilia, encompassing cellular and metabolic levels. The results demonstrated that treatment of cells with rose essential oil resulted in the disruption of cell structure and leakage of cellular contents. Remarkable changes in the morphology of bacterial cells were observed under both scanning electron microscopy and transmission electron microscopy. At the metabolic level, multiple metabolic pathways were disrupted after rose essential oil treatment, including amino acid metabolism, nucleotide metabolism, and aminoacyl tRNA biosynthesis. These results guide the inhibition mechanism of rose essential oil against S. maltophilia and provide some theoretical basis for developing effective essential oil preservatives.
Adversarial Robustness Improvement for Deep Neural Networks
Authors: Eleftheriadis Charis , Symeonidis Andreas , Katsaros Panagiotis 
Published: September 2023

Abstract
Deep neural networks (DNNs) are key components for the implementation of autonomy in systems that operate in highly complex and unpredictable environments (self-driving cars, smart traffic systems, smart manufacturing etc.). It is well known that DNNs are vulnerable to adversarial examples, i.e. minimal and usually imperceptible perturbations, applied to their inputs, leading to false predictions. This threat poses critical challenges, especially when DNNs are deployed in safety or security-critical systems, and renders as urgent the need for defences that can improve the trustworthiness of DNN functions. Adversarial training has proven effective in improving the robustness of DNNs against a wide range of adversarial perturbations. However, a general framework for adversarial defences is needed that will extend beyond a single dimensional assessment of robustness improvement; it is essential to consider simultaneously several distance metrics and adversarial attack strategies. Using such an approach we report the results from extensive experimentation on adversarial defence methods that could improve DNNs resilense to adversarial threats. We wrap up by introducing a general adversarial training methodology, which according to our experimental results, opens prospects for an holistic defence against a range of diverse types of adversarial perturbations.
Area of hydronephrosis is a useful predictive factor of impacted ureteral stones
Authors: Iwahashi Yuya , Deguchi Ryusuke , Kawabata Hiroki , Muraoka Satoshi , Wakamiya Takahito , Yamashita Shimpei , Kohjimoto Yasuo , Hara Isao 
Published: September 2023

Abstract
Ureteroscopic lithotripsy for impacted stones is challenging, but it is important to predict impacted stones preoperatively. Hydronephrosis, which is evaluated by a grading system, is often apparent in impacted stones. However, the grading system is a qualitative evaluation. We therefore focused on a quantitative evaluation: the area of hydronephrosis. The aim of this study was to investigate whether the area of hydronephrosis could predict impacted stones more accurately than Society for Fetal Urology grade. Between January 2014 and April 2022, 160 patients who underwent ureteroscopic lithotripsy for ureteral stones were retrospectively identified. Impacted stones were defined as stones fixed to the ureteral wall that did not move by means of ureteroscopic manipulation or water pressure. Of the 160 patients, 54 (33.8%) had impacted stones. Comparing patient characteristics, there were significant differences in stone size, ureteral wall thickness, Society for Fetal Urology grade, renal pelvic width and area of hydronephrosis (all P < 0.01). Receiver operating characteristic analysis showed that area of hydronephrosis was the more significant predictive value (area under the curve 0.781, P < 0.01) compared with Society for Fetal Urology grade (area under the curve 0.676, P < 0.01). Multivariate analysis revealed that significant independent predictive factors of impacted stones were thicker ureteral wall thickness and larger area of hydronephrosis (both P < 0.01). Area of hydronephrosis and ureteral wall thickness were significant predictors of impacted stones in patients undergoing ureteroscopic lithotripsy for ureteral stones. These factors may be useful for selecting the treatment and preoperative settings.
Theoretically designing and evaluation of highly efficient small donor molecules for organic solar cells
Authors: Mubarik Adeel , Shafiq Faiza , Wang Hao-Ran , Jiang Jun , Ju Xue-Hai 
Published: September 2023

Abstract
The development of High-efficiency photovoltaic devices are the need of time with increasing demand for energy. Herein, we designed seven small molecule donors (SMDs) with A-π-D-π-A backbones containing various acceptor groups for high-efficiency organic solar cells (OSCs). The molecular engineering was performed through substituting the acceptor group in the synthesized compound (BPR) with another highly efficient acceptor group to improve the photoelectric performance of the molecule. The photovoltaic, optoelectronic, and photophysical properties of the proposed compounds (BP1–BP7) were investigated in comparison to BPR using theoretical approaches (DFT and TD-DFT). The key element for effective OSCs is SMDs' red-shifted absorption. All molecules we designed have red-shifted absorption spectra. The modification of the acceptor fragment of the BPR resulted in a reduced HOMO-LUMO energy gap; thus, the designed compounds (BP1–BP7) had improved optoelectronic responses as compared with the BPR molecule. The various key factors are crucial for efficient SMDs such as exciton binding energy, frontier molecular orbitals (FMOs), absorption maximum (λmax), open circuit voltage (VOC), dipole moment (µ), excitation charge nobilities, and transition density matrix of (BPR, BP1‒BP7) have also been studied. High charge mobility is provided by low reorganizational energy (holes and electrons) values, and all the designed compounds were enhanced in this regard. Low excitation energies, large dipole moment, and high open-circuit voltage suggest that our proposed SMDs are appropriate for high-efficiency OSCs. The superiority of the envisioned molecules is also superior, to experimenters to anticipate future developments in extremely effective OSC devices.
WITHDRAWN: The Impact of COVID-19 in Software Design Activities in the Global Software Engineering-Security Prospective
Authors: Nabi Faisal 
Published: September 2023

Abstract

Background: Global Software Engineering (GSE) extends geographical, temporal, and cultural boundaries in distributed environments. Over the past two decades, GSE research has evolved to manage software development for distributed teams. The COVID- 19 pandemic highlights the need for comprehensive research, particularly during the software design phase, to support team collaboration in distributed development.
Aim: This study systematically analyzes the evolution of research emphasis in the GSE field, specifically exploring on whether the research focuses increasing on software design due to the global pandemic.
Method: We systematically analyzed the existing literature in two phases. In the first phase of our study, we mapped GSE research over the two decades leading to the pandemic (2000-2020). In the second phase, we used the forward snowballing approach to examine the literature on the software design phase published between 2020 and 2022.
Results: The analysis of 592 research studies in the two phases reveals various trends in GSE research. Evaluation research is the most explored research type in methods and processes, and human aspects of development. Despite the paradigm shift caused by the COVID-19 pandemic that increased reliance on distributed teams, results show that while software organizations are extensively studied across all software engineering phases, the software design phase remains one of the least explored areas.
Conclusion: This work highlights the evolving GSE research trends, emphasizing the rising significance of collaborative software design in distributed settings. Our findings address current research gaps and underscore the need for further research on software design activities. This contribution envisions a more collaborative, adaptable GSE field, guiding future research to support distributed teams.
Half dome-shaped carbon nitride nanostructures
Authors: Torre Alessandro La 
Published: September 2023

Abstract
We report on a new form of nanoscale carbon nitride in the shape of single layer half dome structures grown on the step edges of boron nitride sheets. The half dome structures are formed spontaneously at high temperature using Fe2O3 capped with N(CH3)4OH supported on BN sheets. During the combustion process the support, firstly, acted as a reducing agent for the transformation of the iron oxide in metallic iron, secondly, as a source of nitrogen that permitted the transformation of the organic capping agent in sp1 CN chains linked with sp2 CN domains. During the Ostwald ripening processes smaller nanoparticles migrates towards bigger nanoparticle, when the nanoparticles come across the step edges of few layer boron nitrides sheets the half dome structure is formed. This new method of synthesis has demonstrated for the first time the formation of half dome structures containing cyanopolyynes sp1 CN chains which link with CN sp2 domains.
Examining the Intersection of Ethnoracial Disparities and HIV Status in Substance Use Risks among U.S. Adults
Authors: Hai Audrey Hang , Batey David Scott , Lee Christina S , Li Stacey , Schnall Rebecca 
Published: September 2023

Abstract

Background
Black and Hispanic Americans experience HIV-related disparities. Substance use might be a contributing factor to these disparities, but there is limited research on this topic. This study investigated various substance use risks by HIV status and race/ethnicity (Black, Hispanic, White) among U.S. adults.
Methods
We used data from the 2005–2019 National Survey on Drug Use and Health (N = 541,921). In each racial/ethnic group, the prevalence rates of past-year and past-month tobacco, alcohol, cannabis, and cocaine use, and past-year alcohol and illicit drug use disorders were estimated by HIV status. A series of logistic regressions with the interaction term of HIV x race/ethnicity were performed to examine race/ethnicity’s moderating effect on the HIV-substance use associations, while controlling for sociodemographic factors and survey year.
Results
Moderation analysis showed that HIV status’s association with the risks of past-year tobacco use (AOR = 1.67, 95% CI = 1.01–2.75), past-year cocaine use (AOR = 3.80, 95% CI = 1.91–7.57), past-month cocaine use (AOR = 5.34, 95% CI = 2.10–13.60), and past-year alcohol use disorder (AOR = 2.52, 95% CI = 1.29–4.92) differed significantly between Black and White adults. Between the Hispanic and White groups, HIV status’s association with the risks of past-year alcohol use (AOR = 2.00, 95% CI = 1.09–3.69), past-year cocaine use (AOR = 2.40, 95% CI = 1.06–5.39), and past-month cocaine use (AOR = 3.69, 95% CI = 1.36–10.02) also differed significantly.
Conclusions
It is well-established that individuals with HIV face an elevated risk of substance use. Our study added valuable insights by highlighting that this phenomenon is particularly more significant among Black and Hispanic adults for several substances when compared to White adults. Implications for practice are discussed.
Local Dynamic Update Methods for 3D Geological Body Structure Model and Voxel Model
Authors: Tian Yiping , Xiao Shengkun , Zhang Rui , Weng Zhengping , Wu Xuechao , Wu Yongjin 
Published: September 2023

Abstract
Due to the complexity of geological structures, the uncertainty of geological phenomena, the massive amount of geological data, and the diversity of geological models, local dynamic updates of 3D geological body models are very difficult. Based on the analysis of the current research status of 3D geological modeling and local dynamic update of 3D geological body model, the local dynamic update methods of geological body models considering geometric, topological, semantic relationships, and geological feature features for different data sources based on the B-Rep (boundary representation) structure model and the CPG (corner-point grid) voxel model are studied in this paper. The local dynamic update methods for the 3D geological bodies based on the B-Rep structure model for new local drilling and profile data are proposed and implemented. Also the local dynamic update methods for 3D geological bodies based on the CPG voxel model for local new drilling data, new profile data, and new multi-source mixed data are proposed and implemented. Finally, dynamic updates for different algorithms and comparative analysis were completed through experiments.
Malignant Teratoma Arising From Mediastinal Non-Seminomatous Germ Cell Tumor: A Rare Case Report
Authors: Verma Nisha , Mahajan Saurabh 
Published: September 2023

Introduction: Primary mediastinal non-seminomatous germ cell tumors (NSGCT) have a worse prognosis than gonadal germ cell tumors (GCTs). Malignant transformation of teratomatous components of GCT to a somatic malignancy is rare.
Materials and methods: A case of primary mediastinal NSGCT with malignant transformation of a teratoma was seen in a 23 years old male. Resected tumor specimen was received. Tissue processing was done and sections were prepared for Histo Pathological Examination.
Results: Histopathology confirmed NSGCT with yolk sac and teratomatous components. Chemotherapy for GCT transiently normalized serum tumor markers with little effect on the mediastinal mass. Incomplete resection of the residual tumor revealed intermediate grade chondosarcoma. Here we discuss this rare case.
Conclusion: malignant transformation to chondrosarcoma is a rare possibility which needs to be considered while managing the patient of Primary Mediastinal Germ Cell Tumors (PMGCT)