bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine Learning for Dementia Prediction: A Systematic Review and Future Research Directions
Authors: Javeed Ashir , Dallora Ana Luiza , Berglund Johan Sanmartin , Ali Arif , Ali Liaqat , Anderberg Peter 
Published: February 2023

AbstractNowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully provided automated solutions to numerous real-world problems. Healthcare is one of the most important research areas for ML researchers, with the aim of developing automated disease prediction systems. One of the disease detection problems that AI and ML researchers have focused on is dementia detection using ML methods. Numerous automated diagnostic systems based on ML techniques for early prediction of dementia have been proposed in the literature. Few systematic literature reviews (SLR) have been conducted for dementia prediction based on ML techniques in the past. However, these SLR focused on a single type of data modality for the detection of dementia. Hence, the purpose of this study is to conduct a comprehensive evaluation of ML-based automated diagnostic systems considering different types of data modalities such as images, clinical-features, and voice data. We collected the research articles from 2011 to 2022 using the keywords dementia, machine learning, feature selection, data modalities, and automated diagnostic systems. The selected articles were critically analyzed and discussed. It was observed that image data driven ML models yields promising results in terms of dementia prediction compared to other data modalities, i.e., clinical feature-based data and voice data. Furthermore, this SLR highlighted the limitations of the previously proposed automated methods for dementia and presented future directions to overcome these limitations.
SMPD1 gene variants in patients with β-Thalassemia major
Authors: Dursun Fadime Ersoy , Özen Filiz 
Published: February 2023

Abstract
Background
β-thalassemia major and Niemann-Pick diseases have similar clinical and laboratory findings. We aimed to investigate the effects of sphingomyelin phosphodiesterase 1 (SMPD1) gene variants on the clinical and laboratory findings in patients with β-thalassemia major.

Methods and results
This study included 45 patients who were followed up for β-thalassemia major in our clinic. Plasma chitotriosidase, leukocyte acid sphingomyelinase, liver enzymes, ferritin, hemogram, biochemical parameters, SMPD1 gene variant analysis, cardiac T2* MRI, and liver R2 MRI were assessed in all patients. The SMPD1 gene c.132_143del, p.A46_L49del (c.108GCTGGC[4] (p.38AL[4])) (rs3838786) variant was detected in 9 of 45 (20.0%) patients. Plasma chitotriosidase, ferritin, acetyl aminotransferase, and alanine aminotransferase levels were significantly higher in patients with the gene variant than in those without (p < 0.05). Leukocyte acid sphingomyelinase levels were significantly lower in patients with the gene variant than in those without (p < 0.05).

Conclusion
These results imply that the clinical and laboratory findings and some features of disease progression in patients with β-thalassemia major are similar to those of Niemann-Pick disease. They also suggest that SMPD1 gene c.132_143del, p.A46_L49del (c.108GCTGGC[4] (p.38AL[4])) (rs3838786) variant may underlie these clinical findings in patients with β-thalassemia major.
How I treat recurrent pediatric high-grade glioma (pHGG): a Europe-wide survey study
Authors: Perwein Thomas , Giese Barbara , Nussbaumer Gunther , von Bueren André O. , van Buiren Miriam , Benesch Martin , Kramm Christof Maria 
Published: February 2023

Abstract
Purpose
As there is no standard of care treatment for recurrent/progressing pediatric high-grade gliomas (pHGG), we aimed to gain an overview of different treatment strategies.

Methods
In a web-based questionnaire, members of the SIOPE-BTG and the GPOH were surveyed on therapeutic options in four case scenarios (children/adolescents with recurrent/progressing HGG).

Results
139 clinicians with experience in pediatric neuro-oncology from 22 European countries participated in the survey. Most respondents preferred further oncological treatment in three out of four cases and chose palliative care in one case with marked symptoms. Depending on the case, 8–92% would initiate a re-resection (preferably hemispheric pHGG), combined with molecular diagnostics. Throughout all case scenarios, 55–77% recommended (re-)irradiation, preferably local radiotherapy > 20 Gy. Most respondents would participate in clinical trials and use targeted therapy (79–99%), depending on molecular genetic findings (BRAF alterations: BRAF/MEK inhibitor, 64–88%; EGFR overexpression: anti-EGFR treatment, 46%; CDKN2A deletion: CDK inhibitor, 18%; SMARCB1 deletion: EZH2 inhibitor, 12%). 31–72% would administer chemotherapy (CCNU, 17%; PCV, 8%; temozolomide, 19%; oral etoposide/trofosfamide, 8%), and 20–69% proposed immunotherapy (checkpoint inhibitors, 30%; tumor vaccines, 16%). Depending on the individual case, respondents would also include bevacizumab (6–18%), HDAC inhibitors (4–15%), tumor-treating fields (1–26%), and intraventricular chemotherapy (4–24%).

Conclusion
In each case, experts would combine conventional multimodal treatment concepts, including re-irradiation, with targeted therapy based on molecular genetic findings. International cooperative trials combining a (chemo-)therapy backbone with targeted therapy approaches for defined subgroups may help to gain valid clinical data and improve treatment in pediatric patients with recurrent/progressing HGG.
Occupation–Education Mismatch of Immigrant Women in Europe
Authors: Akgüç Mehtap , Parasnis Jaai 
Published: February 2023

AbstractAgainst the background of continuing gains in female education and labour market participation and rising migration, we investigate whether women work in occupations which match their educational qualifications and whether migrant women face double penalty in being overqualified for their jobs. Using the data from the European Social Survey covering 2002–2020 with detailed information about occupation and educational attainment, we show that migrant women are significantly more likely to be overqualified in their jobs relative to native women. We explore the role of individual, institutional and workplace factors, as well as attitudes, to explain the overeducation of foreign-born women compared to native-born women. While parental education, workplace and destination country characteristics are all important factors in women’s overqualification, they do not explain the immigrant women’s disadvantage. The overqualification of migrant women is particularly notable amongst low and medium skill groups and in middle income households. These results inform the policy efforts to mitigate the skills waste of migrant women by documenting the gaps, identifying the target groups and suggesting potential channels.
The genus Capparis L. (Capparaceae) in Laos and Cambodia
Authors: Fici Silvio 
Published: February 2023

SummaryA taxonomic revision of the genus Capparis in Laos and Cambodia was undertaken. Based on examination of historical and recent herbarium collections coupled with field investigations, 25 species and 7 intraspecific taxa, all belonging to sect. Monostichocalyx, were recognised in the study area. Among these, a new species, C. averyanovii, and a new subspecies, C. acutifolia subsp. thamphae, from central and northern Laos are described and illustrated. A key to the species is provided, along with descriptions, synonyms, distribution ranges, autecological and phenological data, and 31 lectotypes are selected. When available, vernacular names and traditional uses of the species are also given, based on information from herbarium labels or bibliography. The occurrence of various taxa known only from type material is underlined. Based on the available data, C. diffusa and C. rotundifolia, two species formerly recorded from Cambodia, are excluded from the flora of the study area.
Review of machine learning application in mine blasting
Authors: Abd Elwahab Ahmed , Topal Erkan , Jang Hyong Doo 
Published: February 2023

AbstractMine blasting has adopted machine learning (ML) into its practices with the aims of performance optimization, better decision-making process, and work safety. This study is aimed at reviewing the status of ML method applications to mine blasting issues. One of the most important observations of this research highlights the developed ML methods such as hybrids/ensembles, outperforming the other methods at 61% of the sample of case studies. The first section provides a background on the application of ML methods in mining. Two sections of the review provide the trends in the application of ML methods and the utilization of input parameters in surface and underground blasting problems. The appraisal reveals an increase of hybrid/ensemble or highly developed ML methods for the top four blast issues on the surface (72%) and underground (45%). The sample of studies reviewed indicated through graphical/statistical means a continuing increase in hybrids/ensembles’ use mirrored by high research output for the top four surface blast issues. This is contrasted by a low rate of research in underground blasting, under the encountered operational conditions applied. Regarding the input parameters, controllable parameters (blast design and geometry) were recognized to be steadily used in surface blasting for the top four surface blast issues, along with less involvement from the uncontrollable parameters (geological and geotechnical parameters). On the contrary, underground blasting has a slight involvement of the uncontrollable parameters more than the controllable parameters, in the top four blast issues. In the final section of this paper, the review offers a discussion of the current state of research under the encountered limits and where the efforts should be focused concerning ML methods applied, input parameters involved, and the challenges faced. Such high levels of performances are in demand in a highly complex mining environment. Persistent research, and development of mining employees’ technological skills alongside an increased awareness among mining industry of the benefits of highly developed ML techniques, is greatly needed at this stage. This would establish the role of highly developed ML methods in improving both the blasting process and the overall decision-making and mining management.
Old crimes reported in new bottles: the disclosure of child sexual abuse on Twitter through the case #MeTooInceste
Authors: Aguerri Jesús C. , Molnar Lorena , Miró-Llinares Fernando 
Published: February 2023

AbstractMovements such as #MeToo have shown how an online trend can become the vehicle for collectively sharing personal experiences of sexual victimisation that often remains unreported to the criminal justice system. These social media trends offer new opportunities to social scientists who investigate complex phenomena that, despite existing since time immemorial, are still taboo and difficult to access. They also bring technical difficulties, as the challenge to identify reports of victimisation, and new questions about the characteristic of the events, the role that victimisation testimonies play and the capacity to detect them by analysing their characteristics. To address these issues, we collected 91,501 tweets under the hashtag #MeTooInceste, posted from the 20 to 27 January 2021. A model was fitted using Latent Dirichlet Allocation that detected 1688 tweets disclosing experiences of child sexual abuse, with an accuracy of 91.3% [± 3%] and a recall of 93.1% [± 5%]. We performed Conjunctive Analysis of Case Configurations on the tweets identified as disclosures of victimisation and found that long tweets posted by users with small accounts, without URL or picture, were more likely to be related to disclosure of child sexual abuse. We discuss the possibilities of these trends and techniques offer for research and practice.
Estimating hydrogen usage of a Crew Transport Vessel fleet for Offshore Windfarm maintenance
Authors: Cramer Habbo , Fitz Annika , Niemi Arto , Skobiej Bartosz , Sill Torres Frank 
Published: February 2023

AbstractThis paper presents an estimate for the mass of hydrogen that would be needed to power the current fleet of Crew Transport Vessels (CTVs) used for maintaining the German offshore wind farms and how this demand may be geographically distributed. The estimate is based on a calculation of the marine diesel oil consumption of the current fleet, which is further employed for estimating the current emissions of these activities. Based on the predicted price of hydrogen, bunkering the CTV fleet with hydrogen may become economically advantageous in the future. Moreover, using hydrogen may reduce CO2 emissions. Results have been obtained by using vessel position data, weather data, and diesel consumption estimates. As a shortcoming, certain effects are excluded from the current estimate. However, this work presents an approach that can be improved and used for estimating hydrogen consumption in future scenarios. In these scenarios, a vessel type and parameters can be set. While here the challenge was to create a generic model that can be applied to multiple types of vessels.
Drawing a line?—Visuo-constructive function as discriminator between healthy individuals, subjective cognitive decline, mild cognitive impairment and Alzheimer’s disease and predictor of disease progress compared to a multimodal approach
Authors: Tokaj Amelie , Lehrner Johann 
Published: February 2023

Summary
Purpose
One cognitive domain impaired in Alzheimer’s disease (AD) is visuo-construction. The Vienna Visuo-constructional Test 3.0 Screening (VVT 3.0 Screening) measures this cognitive domain. This study examines how it works in the differentiation of AD from healthy controls (HC) and the prodromal stages subjective cognitive decline (SCD) and mild cognitive impairment (MCI) and also how it performs in prediction of progress compared to the Mini Mental State Examination (MMSE) and the Sunderland Clock Drawing Test (CDT).

Methods
Data from 622 patients (33 HC, 68 SCD, 301 MCI, 220 AD) who completed all three tests were obtained. Furthermore, 117 patients were examined in a follow-up. Data were analyzed in a retrospective analysis comparing the validity of tests in diagnosis and prediction using receiver operator characteristic (ROC) curves and multinominal logistic regression.

Results
The VVT 3.0 Screening shows some ability to discriminate between AD and all other participants (sensitivity: 62.1%, specificity: 83.1%), while of the three examined tests none was able to predict membership to all experimental groups or to predict disease-progress adequately. As the VVT 3.0 Screening is short, easy to apply and largely language independent, it can be considered an alternative to the MMSE in certain situations.

Conclusions
The VVT 3.0 Screening is useful to discriminate between AD and all other participants and can be an alternative to the MMSE in certain situations.
Fracture of aircraft titanium alloys under high-frequency loading
Authors: Nikitin Alexander D. , Shesterkin Pavel S. , Lopatin Sergey S. 
Published: February 2023

AbstractThe paper is devoted to the problem of fatigue failure of two-phase titanium alloy VT3-1 under the action of high-frequency cyclic loading. Samples for the tests were made from the compressor disk of aviation engine D30-Ku installed on Tupolev Tu-154 planes. Repeated alternating loading was carried out by displacements of small amplitude at 20 kHz, coinciding with the first harmonic of longitudinal elastic vibrations of the sample. Analysis of specimen fracture surfaces shows predominant subsurface fracture. Analysis of areas of fatigue nucleation allows identifying elements of microstructure associated with crack nucleation. The results of the study can be used in the interpretation of fracture scenarios of structural elements in operation. Increasing the resource of products under such loads is possible through the use of damping layers or tapes, where possible.
RETRACTED ARTICLE: Synchronous restoration of video key frame loss based on digital media communication protocol
Authors: Li Feng 
Published: February 2023

AbstractThis paper presents a synchronous recovery method for video key frame loss, aiming to analyze the experimental video through digital media feature extraction algorithm. By analyzing and designing effective communication protocols in real-time embedded systems, video data can be better processed. On this basis, key frames are restore synchronously through digital media communication protocol, and verified by comparing with other algorithms. Experimental results shows that the recall and precision of this algorithm for key frame extraction are 90.1% and 100% respectively, Among the three algorithms compared, the recall and precision of video key frame extraction based on single feature algorithm are the highest, 80.2% and 85.9% respectively. At the same time, the synchronization restoration time of this algorithm for lost key frames is 12.2 s, which took less time than other algorithms. It can be seen that the algorithm based on digital media feature extraction is of great significance for synchronous restoration of video key frame loss. It can be seen that the algorithm based on digital media feature extraction is of great significance for the synchronous recovery of video key frame loss, and can effectively promote the development of video data diversity and the improvement of information interaction. Under the digital media communication protocol, it can effectively synchronize the audio and video receiving end of multimedia information, and then recover and predict the lost frames in the video sequence. First, it can enhance the internal characteristics of video frames and the similarity and consistency of images between frames. Secondly, it can significantly improve the accuracy and efficiency of video data processing. Finally, from the perspective of practical development, the synchronous recovery of video key frame loss based on digital media communication protocol can effectively promote the sustainable development of media data, which has certain social value and practical significance in the current era of big data.
Critical success factor of PPP for affordable housing provision in Makkah, Saudi Arabia
Authors: Alshahrani Adnan , Alaboud Naif , Ahmed Yahaya , Karban Abdullah , Majrashi Abdurahman A. , Altowerqi Zayed 
Published: February 2023

AbstractSaudi Arabia recently established public–private partnerships (PPPs) in order to increase the private sector’s involvement in financing and providing affordable housing. However, the successful implementation of the PPP for affordable housing in Makkah necessitates careful consideration of possible barriers. As a result, the purpose of this study is to assess the critical success factor of the PPP and to introduce a housing affordable model for the low-income community. The survey method was used in the study to determine the critical success factors of PPP for affordable housing provision, with participants from both the private and public sectors. Using a five-point Likert scale, respondents were asked to rate the degree of influence of prospective critical success factors of PPP. The data gathered was analyzed using statistical tools. The study’s findings describe the critical success factors of public–private partnerships for affordable housing and establish the critical success factors of the PPP model for affordable housing in Makkah. As a result, determining the critical success factors and suggesting a way forward for the government to effectively provide affordable housing for low-income groups, as has been successful in other parts of countries such as the United Kingdom, Australia, and India, among others.
Urban mining. Scoping resources for circular construction
Authors: Markopoulou Areti , Taut Oana 
Published: February 2023

AbstractOperating with an abundance mindset – rather than from a place of “scarcity” – is a new paradigm, relevant to the practices of design and construction, which expands the definition of “resources” as well as where resources, both raw and non-raw materials, can be found and “mined”.Within three scales of design and planning, the current research – developed at the Institute for Advanced Architecture of Catalonia (IAAC) – examines the applications of computational technologies and life cycle assessment with the goal of setting up protocols for enhancing processes of urban mining and material reuse in future circular construction. In the material scale (i), selected projects experiment with up-cycled waste for the creation of new engineered composites for construction. In the building scale (ii), robotic technologies and computer vision are used to scan and sort the materials from existing buildings or demolition sites. Finally, in the urban scale (iii), google images, satellite data and ML are used to index the existing material stock in building façades in cities.The research calls for agents involved in design, planning and construction to shift their focus to the anthroposphere as a source of, rather than just a destination for, processed goods. The concept of “urban mining” is revisited to manage the material stock in urban systems and the use of anthropogenic resources in new production cycles.Through a multi-scalar approach, the outcome challenges the foundation of our material practices, presenting the potential to disrupt linear patterns of design and making in the built environment.
Presenteeism as a moral hazard problem: Implications for the human resource management
Authors: Ollo-López Andrea , Nuñez Imanol 
Published: February 2023

AbstractInformation asymmetry about the employee's state of health means that workers may decide to work (or not) when they are sick, which turns presenteeism into a principal-agent relationship. From this new perspective, presenteeism can be explained by some distinct and original factors such as implicit incentives related to motivation and a sense of autonomy (empowerment, job usefulness, and recognition) and explicit incentives given by wages and other non-economic benefits (training and career prospects). In a sample of European workers using multilevel (by country) Tobit models, we find that short-term incentives and workers' empowerment increase presenteeism, while long-term incentives reduce it. As expected, supervision is ineffective in controlling presenteeism, while relationships based on trust have a positive impact. Finally, we propose several practices related to incentives, training, monitoring, occupational health and safety and job design specifically intended to manage presenteeism and its consequences in six areas of the human resources function.