bluuebunny/crossref_metadata_2025_split huggingface dataset:
Public Debts’ Component and Crowding Out Effect of Private Domestic Investment in Nigeria
Authors: Michael Eze Onyebuchi , Kingsley Ubaka Chika 
Published: January 2023

Abstract
The study interrogated the rationale behind the federal government’s continued reliance on Keynesian fiscal policy prescriptions of deficit financing as a way of spurring sustainable economic growth in a developing economy like Nigeria; especially when such ideology seemed to contrast sharply with the realities of dwindling growth indices. Thus, this study examined the influence of public debts on the crowding-out effect of private domestic investment in Nigeria from 1986 to 2021. The research used the autoregressive distributed lag (ARDL) model in the analysis. Data obtained from the Central Bank of Nigeria statistical bulletin, volume 32, 2021 on external debt, external debt service, domestic debt, domestic debt service, interest rate, and exchange rate were estimated in the study. The results indicated that external debt and external debt servicing had significant negative effects on private domestic investment; while domestic debt exerted an insignificant positive influence on domestic investment. The result implies that servicing of external debt crowds out private domestic investment in Nigeria. Hence, the government should curtail future contraction of external debt, as any further external debt contraction would lead Nigeria into debt overhang, where future borrowing would almost be impossible for the country.
The prevalence of back pain in patients operated on due to colorectal cancer depending on the type of surgical procedure performed
Authors: Głowacka-Mrotek Iwona , Jankowski Michał , Skonieczny Bartosz , Tarkowska Magdalena , Ratuszek-Sadowska Dorota , Lewandowska Anna , Nowikiewicz Tomasz , Zegarski Wojciech , Mackiewicz-Milewska Magdalena , Ogurkowski Karol 
Published: January 2023

AbstractPurpose Low back pain presents a serious challenge for numerous medical specialties. The purpose of this study was to assess disability due to low back pain in patients operated on due to colorectal cancer depending on the type of surgery performed. Methods This prospective observational study was carried out in the period of July 2019 through March 2020. Included in the study were patients with colorectal cancer for scheduled surgeries including anterior resection of rectum (AR), laparoscopic anterior resection of rectum (LAR), Hartmann’s procedure (HART), or abdominoperineal resection of rectum (APR). The Oswestry Low Back Pain Disability Questionnaire was used as the research tool. The study patients were surveyed at three time points: before surgery, six months after surgery, and one year after surgery. Results The analysis of study results revealed that an increase in the degree of disability and functioning impairment occurred in all groups between time points I and II, with the differences being statistically significant (p<0.05). The inter-group comparative analysis of the total Oswestry questionnaire scores revealed statistically significant differences, with the impairment of function being most severe within the APR group and least severe within the LAR group. Conclusion The study results show that low back pain contributes to impaired functioning of patients operated on due to colorectal cancer regardless of the type of procedure performed. A reduction in the degree of disability due to low back pain was observed one year after the procedure in patients having undergone LAR.
Improving the Care Seeking Behaviour Toward Cervical Cancer Screening Participation Among Gwafan Community Women, North- Central, Nigeria
Authors: Ari Eunice Samuel , Dioso Regidor III Poblete , Sotunsa John Obafemi 
Published: January 2023

Abstract
Introduction: Cervical cancer is the fourth most common cancer in women globally and the second in low-Middle income countries, its screening rate is yet to reach 70% WHO target. Most interventions that proved effective in improving screening participation in some communities did not achieve the desired behavioural outcome in some settings. Aim: This study aimed at evaluating the care seeking behaviour interventions on cervical cancer screening participation. Method: A Pragmatic Multiphase Mixed Methods Design was adopted for this study and three phases of Human Centered Design process was used for data collection. Thematic analysis was used for qualitative data while SPSS for the quantitative data analysis. Results: Findings indicate that most (57.4%) participants were within 30–65 years, most (81.0%) were extremely poor with annual income < 284,700.00 Naira. Before intervention, most (77.4%) were afraid of exposing their private parts, 75.9% were afraid of being diagnosed with cervical cancer; 52.1% felt the procedure was embarrassing, 53.2% felt the procedure was painful; 11.2% had ever screened; majority (88.8%) said involving husband, (86.5%) welcoming attitude of care provider are among facilitators for screening. Screening participation improved from 11.2% preintervention to 29.7% postintervention (average mean screening score from 1.89 ± 0.316 to 1.7000 ± 0.458), all participants who screened postintervention said the procedure was not embarrassing, painful, and were not afraid of procedure and screening room. In conclusion, screening habit in the community was low preintervention as this may result from social norms, affect, utility, influence of sociodemographic variables and lack of facilitating conditions. Care-seeking behaviour interventions has significantly increased screening participation.
Thermal optima of cercarial emergence in trematodes from a marine high-temperature ecosystem, the Persian Gulf
Authors: Khosravi Maral , Díaz-Morales Dakeishla M. , Thieltges David W. , Wahl Martin , Vajedsamiei Jahangir 
Published: January 2023

Abstract
Global warming may alter the dynamics of infectious diseases by affecting important steps in the transmission of pathogens and parasites. In trematode parasites, the emergence of cercarial stages from their hosts is temperature-dependent, being highest around a thermal optimum. If environmental temperatures exceed this optimum as a consequence of global warming, this may affect cercarial transmission. However, our knowledge of cercarial emergence patterns of species from high temperature environments is currently very limited. Here, we investigated the effect of temperature on the emergence of two common trematode species from an abundant mud snail Pirenella cingulata in the Persian Gulf, the warmest sea on Earth. Infected snails were incubated in the laboratory at 6 temperatures from 10 to 40°C for 3 days. We found an optimal temperature for cercarial emergence of 32.0°C and 33.5°C for Acanthotrema tridactyla and Cyathocotylidae gen. sp., respectively, which are the warmest recorded thermal optima for any aquatic trematode species. Emergence of both species dropped at 40°C, suggesting upper thermal limits to emergence. Overall, Persian Gulf trematodes may be among the most heat-tolerant marine trematode species, indicating a potential for dispersing to regions that will continue to warm in the future.
Classification of Catheters and Tubes on Chest Radiographs Using Light-Weight Deep Convolutional Neural Networks
Authors: Wu Jia-Min , Lai Chih-Chun , Chen Sui-Pi , Lee Cheng-Chun , Huang Tung-Kuo , Tseng Neng-Chuan , Tsai Wei-Lin , Lin Yi-Chen , Wu Yen-Cheng , Cheng Bor-Wen , Yu Jen-Ta 
Published: January 2023

Abstract
Purpose: The research aimed to verify the applicability of low computational complexity and high diagnosis accuracy deep convolutional neural network, using MobileNetV2 to identify the presence of chest catheters and tubes on chest X-ray images.
Methods: The dataset of chest X-rays collected from a teaching hospital included the endotracheal tube (ETT), the central venous catheter (CVC), and the nasogastric tube (NGT) datasets. A new method of applying dynamic image size training procedures was implemented and compared with fixed image size training. The idea is to learn more features through dynamic image size training. Transfer learning with pre-trained MobileNetV2 on ImageNet was conducted to accelerate the training process and acquire higher accuracy. Class activation mapping (CAM) was also employed to visualize artificial intelligence (AI) predictions, making AI decisions more explainable.
Results: The ETT datasets included 10464 X-ray images, while the CVC and NGT datasets contained 10274 and 9610 images, respectively. The accuracies for ETT, CVC, and NGT are 99.0%, 98.4%, and 96.2% in the validation dataset, while in the testing dataset are 98.8%, 98.6%, and 96.8%, respectively. The area under the receiver operating characteristics (AUROCs) were 0.992, 0.988, and 0.980 in the ETT, CVC, and NGT testing datasets.
Conclusion: MobileNetV2 with the dynamic image size achieved dedicated performance in the application of chest catheters and tubes classifications. The similarity of the accuracy between the validation and testing data suggests the good generalization capability of the model.
Approaches, tools, algorithms, and methods for automatic term extraction: A systematic literature mapping
Authors: Andrade Juan Carlos Blandón , Otálvaro Carlos Mario Medina , Jaramillo Carlos Mario Zapata , Ríos Alejandro Morales 
Published: January 2023

Abstract

Automatic term extraction is a branch of Natural Language Processing (NLP) used to automatically generate lexicographic materials, such as glossaries, vocabularies, and dictionaries. It allows the creation of standard bases for building unified theories and translations between languages. Scientific literature shows great interest in the construction of automatic term extractors and includes several approaches, tools, algorithms, and methods that can be used for their construction; however, the number of articles in specialized databases is vast, and literature reviews are not recent. This paper presents a systematic literature mapping of the existing material for developing automatic term extractors to provide an overview of approaches, tools, algorithms, and methods used to create them. For this purpose, scientific articles in the domain published between 2015 and 2022 are reviewed and categorized. The mapping results show that among the most used approaches are statistical, with 21.85%; linguistic, with 9.75%; and hybrid, with 68.29%. In addition, there are various computational tools for terminology extraction where authors use different methods for their construction and whose results are measured under the criteria of precision and recall. Finally, 113 documents were selected to answer the research questions and to demonstrate how automatic term extractors are constructed. This paper presents a global summary of primary studies as an essential tool to approach this type of computational system construction.
Integrated Prediction of Potato Cyst Nematodes’ (Globodera rostochiensis and Globodera pallida) Potential Distribution and Risk Regions: Using China as a Case Study
Authors: He Yitong , Wang Guanjin , Ren Yonglin , Zheng Dan , Gao Shan , McKirdy Simon J. , Chu Dong 
Published: January 2023

Abstract
Global potato trade has resulted in the spread of potato cyst nematodes (PCNs) worldwide, which causes significant agricultural and economic loss. Predicting the potential habitats and risk regions for PCNs is critical for management and biosecurity strategies. However, building such prediction models is challenged by the uncertainty of the occurrence data. This research aimed to mitigate the effect of the deficiency of data and build a reliable prediction model of PCNs. The model proposed a combination of fuzzy logic and Maxent modelling enabling the forecasting of the integrated distribution of PCNs. Firstly, the niche similarity between two PCN species was tested by a fuzzy generalised linear model. Then, an integrated dataset was employed to calibrate and evaluate the Maxent model. Results showed that the model constructed on the integrated dataset possessed higher accuracy (Boyce index 0.917) compared to that of individual datasets. After verifying the prediction with the recent incursions in China, the prediction was in accord with actual presence records, which provided further evidence to prove the accuracy of this model. The prediction illustrated that 39% of the land surface in China was suitable for PCNs. The high-risk regions occupied more than half of the cultivated lands, including 66% of the potato-producing areas. In conclusion, the proposed modelling procedure with an integrated dataset can provide an informative reference for countries facing the uncertainty of PCNs’ occurrence to conduct an adequate risk assessment. The integrated prediction result can support policymakers in simultaneously managing both PCN species.
HRAV: Hierarchical virtual machine placement algorithm in multi-hierarchy RF cloud architecture
Authors: Farzaneh Seyed Milad , Fatemi Omid 
Published: January 2023

Abstract
Finding the optimum virtual machine placement (VMP) approach in cloud infrastructure is one of the most important optimization problems. Furthermore, in recent years, with the semiconductor industry's increasing development, there has been a growing interest in fabricated chips, including multiple homogeneous or heterogeneous processing elements (PEs). Modern chips include multiple general-purpose cores alongside reconfigurable fabrics (RFs) used for high-performance computing which perform on par with ASIC hardware. Using RF at different hierarchy levels of cloud architecture significantly improve the performance of VM tasks. The methodology in our previous work is used to design a hierarchical RF-aware VMP. The Communication Delay (CD) parameter is used to perform the optimal virtual machine (VM) placement considering multi-hierarchy RF cloud architecture. The synthetic workload simulation results show that the proposed VMP algorithm outperforms other algorithms that work with our proposed cloud architecture model.
A novel two-stream convolution neural network with temporal information for bearing fault diagnosis
Authors: Ren Hang , Liu Shaogang , Wei Fengmei , Qiu Bo , Zhao Dan 
Published: January 2023

Abstract
Deep learning has been widely applied to intelligent fault diagnosis of rotating machines. In particular, convolutional neural network (CNN) improves the accuracy of diagnosis due to automatic feature extraction ability. However, CNN cannot make full use of the temporal information of the input signals. In order to overcome the above weaknesses, a new depth diagnositic framework called two stream convolution neural network with temporal information(TITSCNN) is proposed for bearing fault diagnosis. First, we obtain tempory signal through the difference of data points in the input signal. Next, tempory signal and original signal are used as input of two CNN branches respectively. Then, an attention mechanism is used to aggregate the features and assign weights to the features extrated by CNN adaptively. Finally, the learned high-level representations are fed into full connect layer to perform fault diagnosis. Experiments are conducted and the results showed that TITSCNN has higher accuracy compared to state-of-the-art methods. Further, experimental results demonstrated that TITSCNN has excellent noise immunity and transformation performance.
Two putative glutamate decarboxylases of Streptococcus pneumoniae as possible antigens for the production of anti-GAD65 antibodies leading to type 1 diabetes mellitus
Authors: García Ernesto 
Published: January 2023

Abstract
Type 1diabetes mellitus (T1DM) has been increasing in prevalence in the last decades and has become a global burden. Autoantibodies against human glutamate decarboxylase (GAD65) are among the first to be detected at the onset of T1DM. Diverse viruses have been proposed to be involved in the triggering of T1DM because of molecular mimicry, i.e., similarity between some viral proteins and one or more epitopes of GAD65. However, the possibility that bacterial proteins might also be responsible of GAD65 mimicry has been seldom investigated. To date, many genomes of Streptococcus pneumoniae (the pneumococcus), a prominent human pathogen particularly among children and the elderly, have been sequenced. A dataset of more than 9000 pneumococcal genomes were mined and two different (albeit related) genes (gadA and gadB), presumably encoding two glutamate decarboxylases similar to GAD65, were found. The various gadASpn alleles were present only in serotype 3 pneumococci belonging to the global lineage GPSC83, although some paralogs have also been discovered in two subspecies of Streptococcus constellatus (pharyngis and viborgensis), an isolate of the group B streptococci, and several strains of Lactobacillus delbrueckii. Besides, gadBSpn alleles are present in > 10% of the isolates in our dataset and represent 16 GPSCs with 123 sequence types and 20 different serotypes. Sequence analyses indicated that gadA- and gadB-like genes have been mobilized among different bacteria either by prophage(s) or by integrative and conjugative element(s), respectively. Substantial similarities appear to exist between the putative pneumococcal glutamate decarboxylases and well-known epitopes of GAD65. These results deserve upcoming studies on the possible involvement of S. pneumoniae in the etiopathogenesis and clinical onset of T1DM.
Non-destructive high-throughput measurement of elastic-viscous properties of maize using a novel ultra-micro sensor array and numerical validation
Authors: Nakashima Taiken , Tomobe Haruka , Morigaki Takumi , Yang Mengfan , Yamaguchi Hiroto , Kato Yoichiro , Vikas Sharma , Kimura Harusato , Morikawa Hitoshi 
Published: January 2023

Abstract
Maize is the world's most produced cereal crop, and the selection of maize cultivars with a high stem elastic modulus is an effective method to prevent cereal crop lodging. We developed an ultra-compact sensor array inspired by earthquake engineering and proposed a method for the high-throughput evaluation of the elastic modulus of maize cultivars. A natural vibration analysis based on the obtained Young's modulus using finite element analysis (FEA) was performed and compared with the experimental results, which showed that the estimated Young's modulus is representative of the individual Young's modulus. FEA also showed the hotspot where the stalk was most deformed when the corn was vibrated by wind. The six tested cultivars were divided into two phenotypic groups based on the position and number of hotspots. In this study, we proposed a non-destructive high-throughput phenotyping technique for estimating the modulus of elasticity of maize stalks and successfully visualized which parts of the stalks should be improved for specific cultivars to prevent lodging.
Multiple founding paternal lineages inferred from the newly-developed 639-plex Y-SNP panel suggested the complex admixture and migration history of Chinese people
Authors: He Guanglin , Wang Mengge , Miao Lei , Chen Jing , Zhao Jie , Sun Qiuxia , Duan Shuhan , Wang Zhiyong , Xu Xiaofei , Sun Yuntao , Liu Yan , Liu Jing , Wang Zheng , Wei Lanhai , Liu Chao , Ye Jian , Wang Le 
Published: January 2023

Abstract
Non-recombining regions of the Y-chromosome recorded the evolutionary traces of male human populations and are inherited haplotype-dependently and male-specifically. Recent whole Y-chromosome sequencing studies have identified previously unrecognized population divergence, expansion and admixture processes, which promotes a better understanding and application of the observed patterns of Y-chromosome genetic diversity. Here, we developed one highest-resolution Y-chromosome Single Nucleotide Polymorphisms (Y-SNP) panel targeted for uniparental genealogy reconstruction and paternal biogeographical ancestry inference, which included 639 phylogenetically informative SNPs (Y-SNPs). We genotyped these loci in 1033 Chinese male individuals from 33 ethnolinguistically diverse populations and identified 257 terminal Y-chromosomal lineages with frequency ranging from 0.010 (singleton) to 0.0687. We identified six dominant common founding lineages associated with different ethnolinguistic backgrounds, which included O2a2b1a1a1a1a1a1a1-M6539, O2a1b1a1a1a1a1a1-F17, O2a2b1a1a1a1a1b1a1b-MF15397, O2a2b2a1b1-A16609, O1b1a1a1a1b2a1a1-F2517, and O2a2b1a1a1a1a1a1-F155. The AMOVA and nucleotide diversity estimates revealed considerable differences and high genetic diversity among ethnolinguistically different populations. We constructed one representative phylogenetic tree among 33 studied populations based on the haplogroup frequency spectrum and sequence variations. Clustering patterns in principal component analysis and multidimensional scaling results showed a genetic differentiation between Tai-Kadai-speaking Li, Mongolic-speaking Mongolian, and other Sinitic-speaking Han Chinese populations. Phylogenetic topology inferred from the BEAST and Network relationships reconstructed from the popART further showed the founding lineages from culturally/linguistically diverse populations, such as C2a/C2b was dominant in Mongolian people and O1a/O1b was dominant in island Li people. We also identified many lineages shared by more than two ethnolinguistically different populations with a high proportion, suggesting their extensive admixture and migration history. Our findings indicated that our developed high-resolution Y-SNP panel included major dominant Y-lineages of Chinese populations from different ethnic groups and geographical regions, which can be used as the primary and powerful tool for forensic practice. We should emphasize the necessity and importance of whole-sequencing of more ethnolinguistically different populations, which can help identify more unrecognized population-specific variations for the final promotion of Y-chromosome-based forensic applications.
Application of the Continuum Suitability Index (CSI) model to display the permeability of the Alpine-Dinaric landscape and to define intervention priorities for ecological linkages
Authors: Favilli Filippo , Laner Peter , Bertoncelj Irena 
Published: January 2023

Abstract
The Alps and the Dinaric Mountains are biodiversity hubs and, although they are subjected to heavy human-related pressures, they still show one of the lowest levels of landscape fragmentation in Europe. The DINALPCONNECT project has the aim of identifying the most important geographical areas for ensuring the biological processes and natural movements and the gene flow of wildlife species between the Alps and the Dinaric Mountains.
The current paper presents the results of the implementation of the Continuum Suitability Index (CSI) model in combination with the least-cost path (LCP) – GIS model in the DINALPCONNECT project area in order to detect the macro-regional ecological connectivity network stretching from the Alps to the Dinaric Mountains. The aim is to support regional decision-makers in defining the actions that will ensure both the ecological network and local human-wildlife coexistence as regards the most important linkages.
The results show that the main core areas (SACA1) of the overall ecological network represent 20% of the total project area. The calculated macro-regional LCP connects 51% of the surface of these areas and reveals great differences in legislation on protected areas between EU and Non-EU countries.
The results show that non-EU countries have the highest shares of SACA1 areas outside protected areas, contributing to important macro-regional connections. The CSI is proving to be a highly adaptable model on the macro-regional level, which can include current and future local issues concerning ecological connections. Therefore, the presented GIS analysis could be a valuable tool enabling regional decision-makers to better manage human and wildlife presence and to identify the best actions for the development of the ecological network.