Search Results (66)

This investigation investigates the influence of a variety of data augmentation techniques on sentiment analysis in low-resource languages, with a particular emphasis on Bulgarian, Croatian, Slovak, and Slovene. The following primary research topic is addressed: is it possible to improve sentiment analysis efficacy in low-resource languages through data augmentation? Our sub-questions look at how different augmentation methods affect performance, how effective WordNet-based augmentation is compared to other methods, and whether lemma-based augmentation techniques can be used, especially for Croatian sentiment tasks. The sentiment-labelled evaluations in the selected languages are included in our data sources, which were curated with additional annotations to standardise labels and mitigate ambiguities. Our findings show that techniques like replacing words with synonyms, masked language model (MLM)-based generation, and permuting and combining sentences can only make training datasets slightly bigger. However, they provide limited improvements in model accuracy for low-resource language sentiment classification. WordNet-based techniques, in particular, exhibit a marginally superior performance compared to other methods; however, they fail to substantially improve classification scores. From a practical perspective, this study emphasises that conventional augmentation techniques may require refinement to address the complex linguistic features that are inherent to low-resource languages, particularly in mixed-sentiment and context-rich instances. Theoretically, our results indicate that future research should concentrate on the development of augmentation strategies that introduce novel syntactic structures rather than solely relying on lexical variations, as current models may not effectively leverage synonymic or lemmatised data. These insights emphasise the nuanced requirements for meaningful data augmentation in low-resource linguistic settings and contribute to the advancement of sentiment analysis approaches. Full article

A country’s development is crucially determined by its cultural and natural heritage, and it is reflected in its industrial structure and its success in the global marketplace. The present paper looks at the global performance of tourism, comparing its performance measured by the Normalised Revealed Comparative Advantage (NRCA) index to the components of natural and cultural heritage, analysing 117 countries of the world. Natural and cultural heritage indicators were derived from the tourism competitiveness reports of the World Economic Forum for the years 2011–2013–2015–2017–2019–2022. Panel regression analysis was applied, with NRCA as the dependent variable and eight indicators of natural and cultural heritage as independent variables, comparing regions of the world. The main findings show considerably differing patterns between regions; Europe and Eurasia being similar to the Americas, with decreasing competitive advantage associated with more focus on endangered species and observance of environmental treaties, while the Middle East and North Africa show a strongly opposite pattern. Cultural heritage has a positive impact only in Sub-Saharan Africa, while Asia and the Pacific benefit mainly from the increase of protected areas and abundance of species. These differences shed light on differences in tourism competitiveness in the global market and may guide policymakers towards utilising heritage items for improving tourism performance. Full article

The Padua temperature series is one of the longest in the world, as daily observations started in 1725 and have continued almost unbroken to the present. Previous works recovered readings from the original logs, and digitalized and corrected observations from errors due to instruments, calibrations, sampling times and exposure. However, the series underwent some changes (location, elevation, observing protocols, and different averaging methods) that affected the homogeneity between sub-series. The aim of this work is to produce a homogenized temperature series for Padua, starting from the results of previous works, and connecting all the periods available. The homogenization of the observations has been carried out with respect to the modern era. A newly released paleo-reanalysis dataset, ModE-RA, is exploited to connect the most ancient data to the recent ones. In particular, the following has been carried out: the 1774–2023 daily mean temperature has been homogenized to the modern data; for the first time, the daily values of 1765–1773 have been merged and homogenized; and the daily observations of the 1725–1764 period have been connected and homogenized to the rest of the series. Snowfall observations, extracted from the same logs from which the temperatures were retrieved, help to verify the robustness of the homogenization procedure by looking at the temperature frequency distribution on snowy days, before and after the correction. The possibility of adding new measurements with no need to apply transformations or homogenization procedures makes it very easy to update the time series and make it immediately available for climate change analysis. Full article

The unique P-band synthetic aperture radar (SAR) instrument, BIOMASS, is scheduled for launch in 2024. This satellite will enhance the estimation of subcanopy topography, owing to its strong penetration and fully polarimetric observation capability. In order to conduct global-scale mapping of the subcanopy topography, it is crucial to calibrate systematic errors of different strips through interferometric SAR (InSAR) DEM (digital elevation model) block adjustment. Furthermore, the BIOMASS mission will operate in repeat-pass interferometric mode, facing the atmospheric delay errors introduced by changes in atmospheric conditions. However, the existing block adjustment methods aim to calibrate systematic errors in bistatic mode, which can avoid possible errors from atmospheric effects through interferometry. Therefore, there is still a lack of systematic error calibration methods under the interference of atmospheric effects. To address this issue, we propose a block adjustment model considering atmospheric effects. Our model begins by employing the sub-aperture decomposition technique to form forward-looking and backward-looking interferograms, then multi-resolution weighted correlation analysis based on sub-aperture interferograms (SA-MRWCA) is utilized to detect atmospheric delay errors. Subsequently, the block adjustment model considering atmospheric effects can be established based on the SA-MRWCA. Finally, we use robust Helmert variance component estimation (RHVCE) to build the posterior stochastic model to improve parameter estimation accuracy. Due to the lack of spaceborne P-band data, this paper utilized L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR data, which is also long-wavelength, to emulate systematic error calibration of the BIOMASS mission. We chose climatically diverse inland regions of Asia and the coastal regions of South America to assess the model’s effectiveness. The results show that the proposed block adjustment model considering atmospheric effects improved accuracy by 72.2% in the inland test site, with root mean square error (RMSE) decreasing from 10.85 m to 3.02 m. Moreover, the accuracy in the coastal test site improved by 80.2%, with RMSE decreasing from 16.19 m to 3.22 m. Full article

Background: The COVID-19 pandemic imposed lockdown measures that affected caregiving. Understanding caregivers’ context provides reveals their adaptive strategies to continue caring in this situation of uncertainty and isolation. Objective: To better understand the caregiving experiences of caregivers looking after dependent individuals living in the community during the pandemic. Design: Qualitative research, phenomenological approach. Setting: Primary healthcare centers in Madrid region (Spain). Participants: 21 family caregivers. Methods: Purposive and theoretical sampling was used to recruit caregivers across nurses from primary healthcare centers. Participants were interviewed using a semi-structured interview guide to explore the caring experience. Interview transcripts were evaluated using thematic analysis. Results: The findings were categorized into two themes: “Caregivers during lockdown—providing care in a time of adversity” and “Caregiving toward normality”. The sub-themes identified were the re-structuring of before-care services and the introduction of new care approaches, managing the dependent person’s health problems, looking after oneself, and dealing with adversity. To adapt to the new normal, strategies were put in place designed to recover confidence and trust, reincorporate assistance, and reconnect with others. Conclusions: Care intensified during the pandemic. Caregivers took on the task without assistance, focusing on preventing contagion and protecting themselves to be able to continue giving care. Full article

Enterovirus (EV) infections are widespread and associated with a range of clinical conditions, from encephalitis to meningitis, gastroenteritis, and acute flaccid paralysis. Knowledge about the circulation of EVs in neonatal age and early infancy is scarce, especially in Africa. This study aimed to unveil the frequency and diversity of EVs circulating in apparently healthy newborns from the Free State Province, South Africa (SA). For this purpose, longitudinally collected faecal specimens (May 2021–February 2022) from a cohort of 17 asymptomatic infants were analysed using metagenomic next-generation sequencing. Overall, seven different non-polio EV (NPEV) subtypes belonging to EV-B and EV-C species were identified, while viruses classified under EV-A and EV-D species could not be characterised at the sub-species level. Additionally, under EV-C species, two vaccine-related poliovirus subtypes (PV1 and PV3) were identified. The most prevalent NPEV species was EV-B (16/17, 94.1%), followed by EV-A (3/17, 17.6%), and EV-D (4/17, 23.5%). Within EV-B, the commonly identified NPEV types included echoviruses 6, 13, 15, and 19 (E6, E13, E15, and E19), and coxsackievirus B2 (CVB2), whereas enterovirus C99 (EV-C99) and coxsackievirus A19 (CVA19) were the only two NPEVs identified under EV-C species. Sabin PV1 and PV3 strains were predominantly detected during the first week of birth and 6–8 week time points, respectively, corresponding with the OPV vaccination schedule in South Africa. A total of 11 complete/near-complete genomes were identified from seven NPEV subtypes, and phylogenetic analysis of the three EV-C99 identified revealed that our strains were closely related to other strains from Cameroon and Brazil, suggesting global distribution of these strains. This study provides an insight into the frequency and diversity of EVs circulating in asymptomatic infants from the Free State Province, with the predominance of subtypes from EV-B and EV-C species. This data will be helpful to researchers looking into strategies for the control and treatment of EV infection. Full article

Introduction: Percutaneous nephrolithotomy (PCNL) is the standard procedure for treating large kidney stones, especially those measuring over 20 mm or staghorn stones. Accurate placement of the tract into the renal collecting system of interest is crucial. Objective: To compare the free-hand puncture technique with robotic-assisted puncture during fluoroscopy-guided PCNL on a phantom kidney model in terms of efficiency and safety. A self-assessment of confidence levels after each puncture was recorded. Study Design: This prospective single-center benchtop study was conducted at the University Malaya Medical Centre (UMMC). Four urological residents participated and performed phantom punctures using both the free-hand bull’s eye technique and the automated needle targeting system with X-ray (ANT-X). Each resident performed a total of 60 punctures on the renal phantom models, with 30 punctures using the free-hand technique and 30 punctures using the ANT-X robotic-assisted system. Results: A total of 240 needle insertions were conducted, with 120 in the ANT-X group and 120 in the free-hand group. The success rate of needle insertions was 100% in both groups. However, the study revealed that the ANT-X group required, on average, an additional 51 s for needle puncture compared to the free-hand group (p < 0.001). In terms of fluoroscopic exposure, the ANT-X group exhibited significantly lower radiation exposure compared to the free-hand group (p < 0.001). Sub-analysis showed that puncture time remained consistent regardless of the technique used, but fluoroscopic screening time decreased with increasing participant experience. The ANT-X group also resulted in significantly lower radiation exposure during initial sessions compared to the free-hand technique. Surgeons’ self-assessment of confidence levels indicated a high level of confidence in needle puncture. Conclusions: Our benchtop study comparing the efficacy and safety between free-hand and ANT-X phantom punctures revealed comparable results. The needle puncture technique facilitated by the ANT-X system showed promising results in terms of reducing fluoroscopic exposure, albeit at the cost of longer operative times. This technology holds promise for novice surgeons who are in the early stages of their learning curve and might be useful for experienced surgeons looking to reduce radiation exposure. Full article

Livestock farmers in Sub-Saharan Africa rely on rain-fed agriculture, which exposes them to the risks of agricultural drought. Agricultural drought has become a significant threat to the extreme mortality of livestock, thus negatively impacting social vulnerability and household resilience to agricultural drought and extreme events. Researchers rarely empirically assess the connection between vulnerability and resilience, which are highly related concepts. By measuring and connecting vulnerability and resilience concepts closely related to disasters such as agricultural drought, this article makes a contribution to the body of disaster literature. The study aimed to empirically examine the relationship between smallholder livestock farming households’ social vulnerability and their resilience to agricultural drought. A survey of 217 smallholder livestock farmers was conducted. The Social Vulnerability Index (SVI), the Agricultural Drought Resilience Index (ADRI), and Pearson’s correlation coefficient were used for data analysis. A correlation was identified between resilience to agricultural drought and social vulnerability, indicating that smallholder livestock farmers are more susceptible to harm and lack the means to rebound effectively. Unsurprisingly, the majority of resource-poor smallholder livestock farmers (79%) lack safety nets during agricultural droughts. They are less resilient and more vulnerable households, leading them to social vulnerability. This study provides input/guidance to identify farming households with high social vulnerability and less resilience to threats and their capabilities of recouping and adopting after experiencing an agricultural drought. Additionally, looking at household resilience and social vulnerability to agricultural droughts could provide a way to pinpoint at-risk areas, assisting emergency planners in directing resources and intervention programs to those areas where assistance is most likely to be needed during disasters such as agricultural droughts. This implies that thorough policy intervention programs need to be tailored toward reducing damage or finding the path to recovery. Full article

Arizona has been at the forefront of groundwater management since the establishment of the Groundwater Management Act in 1980. The Central Arizona Groundwater Replenishment District (CAGRD) is a groundwater management mechanism that facilitates development in regions of Central Arizona where the use of groundwater is limited by law. Several stakeholders have raised concerns about some of the CAGRD’s operations; however, stakeholders have yet to agree on the definition of the problems, let alone how the CAGRD might be improved. This study uses statistical and inductive thematic content analysis of a survey to determine (1) the CAGRD issues that stakeholders view as problems and (2) whether opinions differ significantly among different stakeholder groups. This study also uses deductive thematic content analysis to examine semi-structured interviews with CAGRD experts in order to find potential solutions to the CAGRD-related issues that are considered problems by stakeholders. The survey results show that long-term uncertainties related to the availability of renewable water supplies and hydrologic disconnect, where groundwater pumping and replenishment take place in different sub-basins, are stakeholders’ chief concerns. Sector affiliation and CAGRD membership status are associated with stakeholders’ opinions on some, but not all, questions. The potential policy changes offered address problems identified by stakeholders. This research will inform forthcoming policy discussions regarding groundwater management in Central Arizona as the state’s decision makers look to improve the CAGRD in the context of water scarcity exacerbated by climate change. Full article

In the framework of maritime surveillance, vessel detection techniques based on spaceborne synthetic aperture radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. This paper deals with this topic, presenting a novel approach that exploits a cascade application of a pre-screening algorithm and a discrimination phase. Pre-screening is based on a constant false alarm rate (CFAR) detector, whereas discrimination exploits sub-look analysis (SLA). For the first time, the method has been validated with experiments on multi-frequency (C-, X-, and L-band) SAR images, demonstrating a significant reduction of up to 40% in false alarms within highly congested scenarios, along with a notable enhancement of the receiving operating characteristic (ROC) curves. For future synergic exploitation of multiple SAR missions, the developed dataset, composed of Sentinel-1, SAOCOM, and COSMO-SkyMed images, is comprehensive, having images gathered over the same area with a short time lag (below 15 min). Finally, the diversified processing chains and the results for each mission product and scenario are discussed. Being the first dataset of single-look complex (SLC) SAR multi-frequency data, the present work intends to encourage additional investigation in this promising field of research. Full article

E-Government is one area of digitization that has been under way for several years in European countries. In this paper, we focus on identifying different indices that are aimed at measuring digitalization or e-Government. The results of the analysis showed that there are several indices that focus on this area within the EU, such as EGDI, EPI, LOSI, DGI, e-Government benchmark, Eurostat—Internet use, GII, DSGI, Going Digital toolkit, and DESI. Subsequently, the index areas to be used in the DEA method to measure the efficiency of e-Government-related inputs and outputs within the EU were identified. Inputs and outputs were selected logically and then verified using correlation analysis. Among the input and output indices chosen were Internet usage, DSGI, GII, e-Government benchmark, and interaction with public administration online. From the analysis, three inputs and three outputs were used and the models were output oriented. After implementing the correlation, it can be said that the values between the selected sub-variables are suitable for DEA analysis. Two models were chosen for the calculation, namely the CCR and BCC models. The CCR model found 10 states to be efficient and BCC model found 13 states to be efficient. In addition, in the close analysis, we took a closer look at the CCR model’s inference. Countries such as Denmark, Finland, Estonia, Malta, and Portugal were efficient outliers. When comparing the regions within the EU, we can conclude that the countries of Northern Europe are the most efficient in the field of digitalization (e-Government). As many as four countries out of seven are efficient. Full article

The field of astrobiology aims to understand the origin of life on Earth and searches for evidence of life beyond our planet. Although there is agreement on some of the requirements for life on Earth, the exact process by which life emerged from prebiotic conditions is still uncertain, leading to various theories. In order to expand our knowledge of life and our place in the universe, scientists look for signs of life through the use of biosignatures, observations that suggest the presence of past or present life. These biosignatures often require up-close investigation by orbiters and landers, which have been employed in various space missions. Mars, because of its proximity and Earth-like environment, has received the most attention and has been explored using (sub)surface sampling and analysis. Despite its inhospitable surface conditions, Venus has also been the subject of space missions due to the presence of potentially habitable conditions in its atmosphere. In addition, the discovery of habitable environments on icy moons has sparked interest in further study. This article provides an overview of the origin of life on Earth and the astrobiology studies carried out by orbiters and landers. Full article

The goal of this paper is to use the variable returns to scale (VRS)-slacks-based measure (SBM)-data envelopment analysis (DEA) method to compare the energy resilience of different economies and areas. This study looks at the energy resilience scores of 26 economies from Europe, the Americas, and the Asia-Pacific area. It does this by looking at twelve sub-indicators in three dimensions: society, the economy, and the environment. According to the computational results, seventeen of these economies’ total energy resilience achieved top-tier performance. South Korea, ranked 18th, is only second to these seventeen economies and is followed by, among others, Turkey, Luxembourg, Poland, Italy, Belgium, the Slovak Republic, the Czech Republic, and Hungary. Twelve of the twenty European economies, all three American economies, and two Asia-Pacific economies are relatively energy-resilient. There are sixteen economies in society dimensions, seventeen economies in economy dimensions, and seventeen economies in environment dimensions that are relatively energy-resilient. Sub-dimensional improvement suggestions for relatively less energy-resilient economies are provided according to empirical results. The outcome of the research provides policymakers with a benchmark for future policy planning. Due to data limitations, this study cannot benchmark all OECD economies and does not account for sub-dimensional resource inputs. Full article

Urban agriculture (UA) is proposed as a solution to the social and economic challenges presented by cities by providing urban households with food and income using environmentally friendly food production techniques. To date, most analysis of UA has been based on single-city studies. This paper aims to contribute to the literature by using a cross-country approach and by analysing household level data from nine sub-Saharan countries—Burkina Faso (2014), Ethiopia (2013), Ghana (2009), Malawi (2013), Niger 2014, Nigeria (2012), Tanzania (2010) and Uganda (2013). This paper sets out to answer three questions; the first investigates which are the main characteristics of households engaged in urban agriculture; the second looks at the role played by UA in diversifying household diets and reducing household food expenditure; the third examines the heterogeneity in the impact of UA across the food expenditure distribution. Using an inverse-probability weighted regression adjustment method, the results show that households engaged in agriculture reduced expenditure on food and modified their food expenditure profile by spending more on protein rich food -nuts, legumes, fruits, dairy products, meat and poultry. The study also finds substantial variation on the impact of UA across the food expenditure distribution. Full article

The interferometric synthetic aperture radar (InSAR) technique based on time–frequency (TF) analysis has great potential for mapping the forest canopy height model (CHM) at regional and global scales, as it benefits from the additional InSAR observations provided by the sublook decomposition. Meanwhile, due to the wider swath and higher spatial resolution of single-polarization data, InSAR has a higher observation efficiency in comparison with PolInSAR. However, the accuracy of the CHM inversion obtained by the TF-InSAR method is attenuated by its inaccurate coherent scattering modeling and uncertain parameter calculation. Hence, a new approach for CHM estimation based on single-baseline InSAR data and sublook decomposition is proposed in this study. With its derivation of the coherent scattering modeling based on the scattering matrix of sublook observations, a time–frequency based random volume over ground (TF-RVoG) model is proposed to describe the relationship between the sublook coherence and the forest biophysical parameters. Then, a modified three-stage method based on the TF-RVoG model is used for CHM retrieval. Finally, the two-dimensional (2-D) ambiguous error of pure volume coherence caused by residual ground scattering and temporal decorrelation is alleviated in the complex unit circle. The performance of the proposed method was tested with airborne L-band E-SAR data at the Krycklan test site in Northern Sweden. Results show that the modified three-stage method provides a root-mean-square error (RMSE) of 5.61 m using InSAR and 14.3% improvement over the PolInSAR technique with respect to the classical three-stage inversion result. An inversion accuracy of RMSE = 2.54 m is obtained when the spatial heterogeneity of CHM is considered using the proposed method, demonstrating a noticeable improvement of 32.8% compared with results from the existing method which introduces the fixed temporal decorrelation factor. Full article