bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlation Between the SARA and A-T NEST Clinical Severity Scores in Adults with Ataxia-Telangiectasia
Authors: Major Toby , Tiet May Yung , Horvath Rita , Hensiek Anke E. 
Published: April 2023

AbstractAtaxia-Telangiectasia
(A-T) is an autosomal recessive neurodegenerative disease associated with cerebellar ataxia and extrapyramidal features. A-T has a complex and diverse phenotype with varying rates of disease progression. The development of robust natural history studies and therapeutic trials relies on the accurate recording of phenotype using relevant and validated severity of illness indexes. We compared the commonly used Scale for the Assessment and Rating of Ataxia (SARA) and the disease-specific A-T Neurological Examination Scale Toolkit (A-T NEST), in our adult A-T cohort. We found a strong correlation between A-T NEST and the established SARA score, validating the use of A-T NEST and SARA in capturing the natural history of A-T patients.
Big effort, little gain for users: lessons from the public transport system reform in Bogotá
Authors: Rodriguez-Valencia Alvaro , Rosas-Satizábal Daniel , Hidalgo Darío 
Published: April 2023

AbstractSemi-regulated, privately-operated public transport (PT) systems are common in low and middle-income countries of the Global South. Several cities are now planning or implementing formalized schemes intended to improve quality of service, safety, security of PT services and to reduce negative externalities, with limited success. Bogotá, which embarked on a progressive citywide PT reform process starting in 2009, replicates the negative experience of other large cities introducing citywide transit reforms. The new formalized scheme was implemented gradually between 2012 and 2021. As a result two types of services coexisted in the city for nine years: semiformal and formalized services. This resembled a natural experiment that provided a unique situation to evaluate the restructuring reform in Bogotá from the user’s perspective. This study analyzes passenger satisfaction surveys for both systems by means of ordered Probit models and Importance-Performance Analysis. Despite the good intentions behind the formalization process, results show that users provide better ratings to the traditional semi-regulated services than the new formalized system, mainly because bus frequency and fares are worse and expected improvements in road safety, personal security and comfort have not been delivered. The reform in Bogotá allowed the city to have resilience during the pandemic, though; and provided a framework for inclusion of zero and low-emission buses. The analysis suggests some recommendations for the improvement of transit reform processes: putting the focus on service quality, as well as assigning sufficient funding and developing institutional capacities to undertake the required changes.
Raman spectroscopy for viral diagnostics
Authors: Lukose Jijo , Barik Ajaya Kumar , Mithun N  , Sanoop Pavithran M  , George Sajan D. , Murukeshan V. M. , Chidangil Santhosh 
Published: April 2023

AbstractRaman spectroscopy offers the potential for fingerprinting biological molecules at ultra-low concentration and therefore has potential for the detection of viruses. Here we review various Raman techniques employed for the investigation of viruses. Different Raman techniques are discussed including conventional Raman spectroscopy, surface-enhanced Raman spectroscopy, Raman tweezer, tip-enhanced Raman Spectroscopy, and coherent anti-Stokes Raman scattering. Surface-enhanced Raman scattering can play an essential role in viral detection by multiplexing nanotechnology, microfluidics, and machine learning for ensuring spectral reproducibility and efficient workflow in sample processing and detection. The application of these techniques to diagnose the SARS-CoV-2 virus is also reviewed.
Graphical abstract
Generative image captioning in Urdu using deep learning
Authors: Afzal Muhammad Kashif , Shardlow Matthew , Tuarob Suppawong , Zaman Farooq , Sarwar Raheem , Ali Mohsen , Aljohani Naif Radi , Lytras Miltiades D. , Nawaz Raheel , Hassan Saeed-Ul 
Published: April 2023

AbstractUrdu is morphologically rich language and lacks the resources available in English. While several studies on the image captioning task in English have been published, this is among the pioneer studies on Urdu generative image captioning. The study makes several key contributions: (i) it presents a new dataset for Urdu image captioning, and (ii) it presents different attention-based architectures for image captioning in the Urdu language. These attention mechanisms are new to the Urdu language, as those have never been used for the Urdu image captioning task (iii) Finally, it performs quantitative and qualitative analysis of the results by studying the impact of different model architectures on Urdu’s image caption generation task. The extensive experiments on the Urdu image caption generation task show encouraging results such as a BLEU-1 score of 72.5, BLEU-2 of 56.9, BLEU-3 of 42.8, and BLEU-4 of 31.6. Finally, we present data and code used in the study for future research via GitHub (https://github.com/saeedhas/Urdu_cap_gen).
Ultra-conserved RNA: a novel biological tool with diagnostic and therapeutic potential
Authors: Wang Tingye , Li Feng , Lu Zhanping 
Published: April 2023

AbstractUltra-conserved RNA (ucRNA) is a subset of long non-coding RNA, that is highly conserved among mice, rats and humans. UcRNA has attracted extensive attention in recent years for its potential biological significance in normal physiological function and diseases. However, due to the instability of RNA and the technical limitation, the function and mechanism of ucRNAs are largely unknown. Over the last two decades, researchers have made a lot of efforts to try to lift the veil of ucRNA in nervous, cardiovascular system and other systems as well as cancers. Since the concept of the glymphatic system is relatively new, we summarized here recent findings on the functions, regulation and the underlying mechanisms of ucRNAs in physiology and pathology. Meanwhile, pathology in some diseases is likely to contribute to abnormal expression of ucRNA in turn. We also discuss the technical challenges and bright prospects for future applications of ucRNAs in the diagnosis and treatment of diseases.
Land use/land cover change impact on streamflow using Arc-SWAT model, in case of Fetam watershed, Abbay Basin, Ethiopia
Authors: Mekonnen Yitbarek Andualem , Manderso Temesgen Mekuriaw 
Published: April 2023

AbstractChanges in Land Use Land Cover (LULC) are currently one of the greatest pressing issues facing the watershed, its hydrological properties of soil, and water management in catchment areas. One of the most important elements impacting streamflow in watersheds is LULC change. The main objective of this study was to evaluate the effect and future predication of LULC change on streamflow of the Fetam watershed by using Cellular Automata (CA)-Markov in IDRISI software. To analyze the impact of land use/cover change on streamflow, the Soil and Water Assessment Tool (SWAT) calibration and validation model was used. LULC map was developed by using Cellular Automata (CA)-Markov in IDRISI software, and the coverage of LULCs was including parameters of cropland, vegetation, grassland, Built-up area/Urban and water body. The findings of this study showed that the major challenges of land use/cove changes were rapid population increase, farming, and industrial activity. During the study period (2000–2020), most portions of the water body, vegetation, and grassland were changed into cropland and constructed by building. Cropland and construction areas increased by 15% and 46.95%, respectively, whereas water bodies, vegetation, and grassland decreased by 62.7%, 70.02%, and 38.1%, respectively. According to the forecasted results for the period of 2030–2040, cropland and built-up areas are increased, while vegetation, grassland, and water bodies were decreased. The SWAT model's calibration and validation performance was evaluated using the streamflow of the most sensitive parameters. For the years 2000–2004, and 2005–2012, the models were calibrated and validated, and the results showed good agreement between observed and simulated streamflow, with NSE and R2 values of 0.88 and 0.72 and 0.9 and 0.85, respectively. The results of this study indicated that the seasonal streamflow was decreased from 2000 to 2010 and 2010–2020 years during the dry and rainy seasons. In general, the impacts of land use/cover change on streamflow are significant considerations for planning and implementing water resource projects. In order to address the risks, effective land-use planning and climate-resilient water management strategies will be improved.
A Dynamic Occupancy Model for Interacting Species with Two Spatial Scales
Authors: Kleiven Eivind Flittie , Barraquand Frédéric , Gimenez Olivier , Henden John-André , Ims Rolf Anker , Soininen Eeva Marjatta , Yoccoz Nigel Gilles 
Published: April 2023

AbstractOccupancy models have been extended to account for either multiple spatial scales or species interactions in a dynamic setting. However, as interacting species (e.g., predators and prey) often operate at different spatial scales, including nested spatial structure might be especially relevant to models of interacting species. Here we bridge these two model frameworks by developing a multi-scale, two-species occupancy model. The model is dynamic, i.e. it estimates initial occupancy, colonization and extinction probabilities—including probabilities conditional to the other species’ presence. With a simulation study, we demonstrate that the model is able to estimate most parameters without marked bias under low, medium and high average occupancy probabilities, as well as low, medium and high detection probabilities, with only a small bias for some parameters in low-detection scenarios. We further evaluate the model’s ability to deal with sparse field data by applying it to a multi-scale camera trapping dataset on a mustelid-rodent predator–prey system. Most parameters are estimated with low uncertainty (i.e. narrow posterior distributions). More broadly, our model framework creates opportunities to explicitly account for the spatial structure found in many spatially nested study designs, and to study interacting species that have contrasting movement ranges with camera traps.Supplementary materials accompanying this paper appear online.
Efficient protection of the Baltic Sea needs a revision of phosphorus metric
Authors: Iho Antti , Valve Helena , Ekholm Petri , Uusitalo Risto , Lehtoranta Jouni , Soinne Helena , Salminen Jani 
Published: April 2023

AbstractEutrophication of the Baltic Sea is driven by phosphorus and nitrogen. While the anthropogenic point source loads of both nutrients have decreased markedly, further reductions are needed. This is true particularly for phosphorus, as highlighted by its stringent abatement targets in HELCOM’s Baltic Sea Action Plan. To meet the targets, more results need to be achieved in non-point source abatement, specifically from agricultural sources. The growing pressure for phosphorus abatement from agriculture may lead to environmentally and economically inefficient outcomes unless we account for the variability in how different forms of phosphorus respond to abatement measures, and how these forms contribute to eutrophication. The precautionary and efficiency improving way to advance policies is to either replace or supplement the Total Phosphorus metric with a metric more accurate in reflecting the biologically available phosphorus. This policy fix becomes more important as the relative share of agricultural emissions of total pollution increases.
Efficient item count techniques with one or two lists
Authors: Quatember Andreas 
Published: April 2023

AbstractIf the direct questioning on sensitive variables leads to non-ignorable item-nonresponse and untruthful answering, a considerably biased estimator might be the consequence. In such cases, indirect questioning designs, which protect the respondents’ privacy by masking the sensitive information, could pay off in terms of accuracy through an increased willingness to cooperate. To achieve this goal, such a design has to be simple in its implementation for the users and easy to understand for the respondents. In this article, it is shown for one of the indirect questioning designs, the item count technique, how the usage of specific oftentimes available prior information can substantially improve the estimation accuracy and at the same time reduce the respondents’ task. This can make the method a stronger and more serious competitor of the direct questioning on sensitive attributes, which is commonly used in empirical research.
Adoption, Adaptation or Exposure? Novel Digital Gambling Activities and Links with Gambling Problems
Authors: Hing Nerilee , Rockloff Matthew , Browne Matthew 
Published: April 2023

Abstract
Purpose of Review
Gambling problems are much more common amongst people who use novel gambling products, including skin gambling, esports betting and fantasy sports betting. The exposure and adaptation effects suggest that, like a novel pathogen, new products produce gambling problems until adaptation can counteract vulnerabilities. The purpose of this review is to posit, based on recent data, that an adoption effect provides a more parsimonious account for why novel gambling products are associated with problems.

Recent Findings
People who are more vulnerable to a gambling problem are more likely to adopt novel gambling forms, consistent with their tendency to gamble on many forms. The high prevalence of gambling problems cannot be accounted for by the exposure effect alone, unless one assumes, implausibly, that these novel forms are dramatically more toxic than established products. As newer products diffuse in their acceptance throughout the population, the proportion of people with a gambling problem who play such games goes down. The evolution of gambling products can be described by a product lifecycle model where gambling problems are common amongst early adopters, but proportionately decrease amongst users as a product grows in popularity, reaches maturity and finally stagnates and is replaced.

Summary
The adoption effect is important because it indicates the need for interventions when new gambling products are introduced. It cautions against assuming that interventions are working just because the prevalence of gambling problems declines.
Construction and analysis of multi-relationship bipartite network model
Authors: Lv Hehe , Zhang Bofeng , Li Tingting , Hu Shengxiang 
Published: April 2023

AbstractBipartite networks that characterize complex relationships among data arise in various domains. The existing bipartite network models are mainly based on a type of relationship between objects, and cannot effectively describe multiple relationships in the real world. In this paper, we propose a multi-relationship bipartite network (MBN) model, which can describe multiple relationships between two types of objects, and realizes simple weighted bipartite network reconstruction. Our model contains three major modules, namely multi-relationship bipartite network modeling (MBNM), multi-relationship aggregation module (MAM) and network reconstruction module (NRM). In MBNM, a multi-relationship bipartite network is proposed to describe multiple relationships between two types of objects. In the MAM, considering that different relationships have different information for the model, we introduce a novel relationship-level attention mechanism, and the aggregation of multiple relationships is carried out through the importance of each relationship. Based on the learning framework, the NRM can learn the potential representations of nodes after multi-relationship aggregation, and design a nonlinear fusion mechanism to reconstruct weighted bipartite network. We conducted extensive experiments on three real-world datasets and the results show that multi-relationship aggregation can effectively improve the performance of the model. In addition, experiments also show that our model can outperform existing competitive baseline method.
Data-driven XGBoost model for maximum stress prediction of additive manufactured lattice structures
Authors: Zhang Zhiwei , Zhang Yuyan , Wen Yintang , Ren Yaxue 
Published: April 2023

AbstractLattice structures created using additive manufacturing technology inevitably produce inherent defects that seriously affect their mechanical properties. Predicting and analysing the effect of defects on the maximum stress is very important for improving the lattice structure design and process. This study mainly used the finite element method to calculate the lattice structure constitutive equation. The increase in defect type and quantity leads to difficulty in modelling and reduces calculation accuracy. We established a data-driven extreme gradient enhancement (XGBoost) with hyperparameter optimization to predict the maximum stress of the lattice structure in additive manufacturing. We used four types of defect characteristics that affect the mechanical properties—the number of layers, thick-dominated struts (oversize), thin-dominated struts (undersizing), and bend-dominated struts (waviness)—as the input parameters of the model. The hyperparameters of the basic XGBoost model were optimised according to the diversity of the inherent defect characteristics of the lattice structure, while the parameters selected by experience were replaced using the Gaussian process method in Bayesian optimization to improve the model’s generalisation ability. The prediction datasets included the type and number of defects obtained via computer tomography and the calculation results of the finite element model with the corresponding defects implanted. The root mean square error and R-squared error of the maximum stress prediction were 17.40 and 0.82, respectively, indicating the effectiveness of the model proposed in this paper. Furthermore, we discussed the influence of the four types of defects on the maximum stress, among which the thick strut defect had the greatest influence.
Sleep quality and sleep deprivation: relationship with academic performance in university students during examination period
Authors: Suardiaz-Muro Maria , Ortega-Moreno Manuel , Morante-Ruiz Miguel , Monroy Manuel , Ruiz Miguel A. , Martín-Plasencia Pilar , Vela-Bueno Antonio 
Published: April 2023

AbstractThe beginning of the university brings together maturational, psychosocial and academic changes that make university students more prone to suffer from insufficient or poor quality sleep, which can negatively influence their academic performance. The period of taking exams is a key part of the academic year. However, there are few studies that analyze sleep during this period of time. Our aim is to study the association of sleep quality and sleep deprivation with academic performance during the examination period. A descriptive, cross-sectional and correlational study was carried out with the participation of 640 subjects in the first three years of five faculties belonging to the Universidad Autónoma de Madrid. The instrument used consisted of a questionnaire that included sociodemographic and academic data, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and information about the academic performance. During the examination period, a positive association was found between sleep quality and academic performance. University students slept less than desired, both on weekdays and weekends, and the sleep debt during the week was associated with a worse students’ perception of their academic performance. In total, 61.3% of the students believed that their performance would improve by getting more sleep. In addition, low drowsiness and napping were also found. In conclusion, during periods of greater academic demand, an insufficient sleep and poor quality is commonly observed, affecting negatively to their academic performance. Actually, about 2/3 of our subjects believed that their performance would improve by getting more sleep.
Probing the mechanism of action (MOA) of Solanum nigrum Linn against breast cancer using network pharmacology and molecular docking
Authors: Song Yingying , Sakharkar Meena Kishore , Yang Jian 
Published: April 2023

AbstractSolanum nigrum Linn is a medicinal herb widely used in traditional Chinese medicine to treat ailments such as fever, inflammation and cancer. Although quite a few compounds have been isolated and characterized, its anticancer mechanism remains elusive. Thus, in this study, we used network pharmacology and molecular docking strategies to identify the major active ingredients in S. nigrum and reveal its putative mechanism against human breast cancer. Six compounds, quercetin, cholesterol, 3-epi-beta-sitosterol, diosgenin, medioresinol and solanocapsine, were identified to be the major active ingredients. Target identification and analysis showed that they regulate 80 breast cancer-related targets. Furthermore, network analysis showed that the six active ingredients regulate multiple pathways including ErbB signaling pathway and estrogen signaling pathway and genes AKT1(AKT serine/threonine kinase 1), ESR1(estrogen receptor 1), EGFR(epidermal growth factor receptor), SRC(proto-oncogene tyrosine-protein kinase Src), AR(androgen receptor) and MMP9(matrix metalloproteinase 9) are crucial genes involved in the regulations. Molecular docking implied that quercetin could form good binding with AKT1, EGFR, SRC and MMP9. Our current study suggests that the anticancer function of S. nigrum is likely via synergistic/additive effects of multiple active ingredients’ regulations of different signaling pathways. Further studies are warranted to establish the standard for S. nuigrum to be used as a CAM (complementary and alternative medicine) in breast cancer treatment and dissect its potential interactions with chemotherapy drugs.